| Version: | 2.9 |
| Type: | Package |
| Title: | International Assessment Data Manager |
| Date: | 2024-01-16 |
| Author: | Daniel Caro <dcarov@gmail.com>, Przemyslaw Biecek <przemyslaw.biecek@gmail.com> |
| Maintainer: | Daniel Caro <dcarov@gmail.com> |
| Description: | Provides tools for importing, merging, and analysing data from international assessment studies (TIMSS, PIRLS, PISA, ICILS, and PIAAC). |
| License: | GPL-2 |
| URL: | https://daniel-caro.com/r-intsvy/, https://github.com/eldafani/intsvy |
| BugReports: | https://github.com/eldafani/intsvy/issues |
| Imports: | dplyr, foreign, ggplot2, Hmisc, memisc, plyr, reshape, stats, utils |
| LazyData: | yes |
| NeedsCompilation: | no |
| Repository: | CRAN |
| Packaged: | 2024-01-16 18:52:10 UTC; eldani |
| Depends: | R (≥ 3.5.0) |
| Date/Publication: | 2024-01-16 23:00:18 UTC |
International Assessment Data Manager
Description
Provides tools for importing, merging, and analysing data from international assessment studies (TIMSS, PIRLS, PISA, and PIAAC and others)
Details
| Package: | intsvy |
| Type: | Package |
| Version: | 2.9 |
| Date: | 2024-01-16 |
| License: | GPL-2 |
intsvy allows useRs to work with international assessment data (e.g., TIMSS, PIRLS, PISA, ICILS, and PIAAC). Data and merge functions print variable labels and the name of participating countries in international assessments as well as import data directly into R for the variables in student, parent, school, and teacher instruments and countries selected by the useR. Analysis functions, including mean statistics, standard deviations, regression estimates, correlation coefficients, and frequency tables, calculate point estimates and standard errors that take into account the complex sample design (i.e., replicate weights) and rotated test forms (i.e., plausible achievement values).
Author(s)
Daniel Caro <dcarov@gmail.com>, Przemyslaw Biecek <przemyslaw.biecek@gmail.com>
References
PISA, PIAAC, PIRLS, and TIMSS Technical Reports
Utility function
Description
Utility function
Usage
adj.input(x, threshold = 0.5)
Arguments
x |
A list element with labels |
threshold |
User defined threshold |
Details
A utility function for PISA data importation
Value
adj.input returns data with corrected labels
Author(s)
Martin Elff
See Also
adj.measlev, is.vlabeled
Examples
## Not run:
## Input of adj.measlev
adj.input(data)
## End(Not run)
Utility function
Description
Removes missing data in as.data.frame(spss.system.file())
Usage
adj.measlev(x, threshold = 0.5)
Arguments
x |
The data.set |
threshold |
User defined threshold |
Details
A utility function for PISA data importation
Value
adj.measlev returns a data.set with corrected measurement levels for as.data.frame
Author(s)
Martin Elff
See Also
adj.input, is.vlabeled
Examples
## Not run:
## Input of adj.measlev
adj.measlev(mydataset)
## End(Not run)
Config files for intsvy studies
Description
Each config file describes detailed study meta-data. Such meta data defined names of columns with weights, type of weighting, number of plausible values and other study parameters. Most of intsvy functions require such config objects.
Usage
pisa_conf
Format
A list with three components - input, variables and parameters.
Performance international benchmarks and proficiency levels
Description
intsvy.ben.pv calculates the percentage of students performing at or above the cut-off points (scores) given by the useR. The default are the benchmarks established by official reports.
Usage
intsvy.ben.pv(pvnames, by, cutoff, data, atlevel=FALSE, export = FALSE, name = "output",
folder = getwd(), config)
Arguments
pvnames |
The names of columns corresponding to the achievement plausible scores, for example, paste0("PV",1:10,"MATH") for PISA |
cutoff |
The cut-off points for the assessment benchmarks (e.g., cutoff= c(357.77, 420.07, 482.38, 544.68, 606.99, 669.30)). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
atlevel |
A logical value. If TRUE, percentages at each level are calculated. Otherwise (FALSE), percentages at or above levels are reported. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
pirls.ben.pv returns a data frame with the percentage of students at or above the benchmark and the corresponding standard error.
See Also
timss.ben.pv, pirls.ben.pv, pisa.ben.pv
Examples
## Not run:
pisa.ben.pv(pvlabel= paste0("PV",1:10,"MATH") for PISA, by="CNT",
data=pisa, atlevel = TRUE)
intsvy.ben.pv(pvnames= paste0("PV",1:10,"MATH") for PISA by="CNT",
data=pisa, atlevel= TRUE, config=pisa_conf)
piaac.ben.pv(pvlabel= paste0("PVLIT", 1:10), by="CNTRYID", data=piaac)
intsvy.ben.pv(pvnames= paste0("PVLIT", 1:10), by="CNTRYID", data=piaac,
config=piaac_conf)
timss.ben.pv(pvlabel= paste0("BSMMAT0", 1:5), by="IDCNTRYL", data=timss4)
intsvy.ben.pv(pvnames= paste0("BSMMAT0", 1:5), by="IDCNTRYL", data=timss4,
config=timss4_conf)
## End(Not run)
Config files for intsvy studies
Description
intsvy.config set non standard parameters for intsvy functions. It allso allo to apply intsvy functions to new studies that are similar to PIRLS, TIMSS, PISA, PIAAC, ICILS.
Usage
intsvy.config(variables.pvlabelpref,
variables.pvlabelsuff,
variables.weight,
variables.jackknifeZone,
variables.jackknifeRep,
parameters.cutoffs,
parameters.cutoffs2,
parameters.percentiles,
parameters.weights,
parameters.PVreps,
parameters.varpv1,
input.type,
input.prefixes,
input.student,
input.student_colnames1,
input.student_colnames2,
input.student_pattern,
input.homeinput,
input.home_colnames,
input.school,
input.school_colnames,
input.teacher,
input.teacher_colnames,
input.student_ids,
input.school_ids,
input.type_part,
input.cnt_part, base.config = pirls_conf)
Arguments
parameters.weights |
Weighting scheme. It may be "JK" for studies like PIRLS, ICLS, TIMSS, or "BRR" for studies like PISA or "mixed_piaac" for studies with mixed design like PIAAC. |
parameters.cutoffs2, parameters.cutoffs |
Cut offs for plausible values, either for benchmar or for logistic regression. |
parameters.percentiles, parameters.PVreps |
Other parameters for weighting schemes, like number of PVs. |
parameters.varpv1 |
Logical value, TRUE if only 1 plausible value for within variance estimation. |
variables.pvlabelpref, variables.pvlabelsuff, variables.weight, variables.jackknifeZone, variables.jackknifeRep |
Names of variables that are used for jack-knife replicates. |
input.type, input.prefixes, input.student, input.student_colnames1, input.student_colnames2, input.student_pattern, input.homeinput, input.home_colnames, input.school, input.school_colnames, input.teacher, input.teacher_colnames, input.student_ids, input.school_ids, input.type_part, input.cnt_part |
Parameters to correctly read data from files downloaded from iea.nl website. |
base.config |
Base config structure, either pirls_conf, pisa_conf, piaac_conf, timss4_conf, timss8_conf, icils_conf. |
Value
intsvy.config returns new object with parameters. It is a list with three components - input, variables and parameters.
Examples
## Not run:
icils_conf <- intsvy.config(input.student_pattern = "^PV[0-5]CIL$" ,
parameters.cutoffs2 = 550, intsvy:::pirls_conf)
icils_conf
## End(Not run)Logistic regression analysis
Description
intsvy.log performs logistic regression analysis for an observed depedent variable (NOT for plausible values)
Usage
intsvy.log(y, x, by, data, export = FALSE, name = "output",
folder = getwd(), config)
Arguments
y |
Label for dependent variable |
x |
Data labels of independent variables (e.g., x = c("ASDHEHLA", "ITSEX") ). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
pirls.log prints a data frame with coefficients, standard errors, t-values, and odds ratios. Results are stored in a list object of class "intsvy.reg".
See Also
timss.log, pirls.log, pisa.log
Examples
## Not run:
pisa$SKIP[!(pisa$ST09Q01 =="None" & pisa$ST115Q01 == "None")] <- 1
pisa$SKIP[pisa$ST09Q01 =="None" & pisa$ST115Q01 == "None"] <- 0
pisa$LATE[!pisa$ST08Q01=="None"] <- 1
pisa$LATE[pisa$ST08Q01=="None"] <- 0
pisa.log(y="SKIP", x="LATE", by="IDCNTRYL", data = pisa)
## End(Not run)
Logistic regression analysis with plausible values
Description
intsvy.log.pv performs logistic regression with plausible values and replicate weights.
Usage
intsvy.log.pv(pvnames, x, cutoff, by, data, export=FALSE, name= "output",
folder=getwd(), config)
Arguments
pvnames |
The names of columns corresponding to the achievement plausible scores. |
x |
Data labels of independent variables. |
cutoff |
The cut-off point at which the dependent plausible values scores are dichotomised (1 is larger than the cut-off) |
by |
The label for the categorical grouping variable (i.e., by="IDCNTRYL") or variables (e.g., x= c("IDCNTRYL", "ITSEX")). |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.log.pv returns a data frame with coefficients, standard errors, t-values, and odds ratios. If "by" is specified, results are reported in a list. Weights, e.g. "TOTWGT" for PIRLS, are defined in the config argument.
See Also
pisa.log.pv, pirls.log.pv, timss.log.pv
Examples
## Not run:
intsvy.log.pv(pvnames=paste0("PV",1:10,"MATH") , cutoff= 606.99, x="ESCS", by="IDCNTRYL",
data=pisa, config=pisa_conf)
intsvy.log.pv(pvnames=paste0("BSMMAT0", 1:5), cutoff= 550, x="ITSEX", by="IDCNTRYL",
data=timss8g, config=timss8_conf)
## End(Not run)Calculates mean of variable
Description
Calculates mean and standard error of observed variable (NOT one with plausible values).
Usage
intsvy.mean(variable, by, data, export = FALSE,
name = "output", folder = getwd(), config)
Arguments
variable |
The label corresponding to the observed variable, for example, "AGE_R" for age of respondent. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNTRYID"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIAAC. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.mean returns a data frame with means and standard errors.
See Also
pisa.mean, timss.mean, pirls.mean
Examples
## Not run:
intsvy.mean(variable="READHOME", by="CNTRYID", data=piaac, config=piaac_conf)
intsvy.mean(variable="PARED", by="IDCNTRYL", data=pisa, config=pisa_conf)
intsvy.mean(variable="BSBGSLM", by='IDCNTRYL', data=timss8g, config=timss8_conf)
intsvy.mean(variable='ASBHELA', by= 'IDCNTRYL', data=pirls,config=pirls_conf)
## End(Not run)
Calculates mean achievement score
Description
The function intsvy.mean.pv uses plausible values to calculate the mean achievement score and its standard error.
Usage
intsvy.mean.pv(pvnames, by, data, export=FALSE, name= "output", folder=getwd(), config)Arguments
pvnames |
The names of columns corresponding to the achievement plausible scores, for example, paste0("PV",1:10,"MATH") for PISA. |
by |
The label for the grouping variable, usually the countries (e.g., by="CNTRYID"), but could be any other categorical variable. |
data |
An R object, normally a data frame. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.mean.pv returns a data frame with means and standard errors.
See Also
pisa.mean.pv, timss.mean.pv, pirls.mean.pv
Examples
## Not run:
intsvy.mean.pv(pvnames = paste0("ASRREA0", 1:5), by= "IDCNTRYL",
data=pirls, config=pirls_conf)
intsvy.mean.pv(pvnames = paste0("PV",1:10,"MATH"), by="CNT", data=pisa,
config=pisa_conf)
intsvy.mean.pv(pvnames = paste0("BSMMAT0", 1:5), by= "IDCNTRYL", data=timss8g,
config=timss8_conf)
intsvy.mean.pv(pvnames = paste0("PVNUM", 1:10), by="CNTRYID", data=piaac,
config=piaac_conf)
## End(Not run)
Calculates percentiles
Description
Calculates percentiles for plausible values
Usage
intsvy.per.pv(pvnames, by, per, data, export=FALSE, name= "output",
folder=getwd(), config)
Arguments
pvnames |
The names of columns corresponding to the achievement plausible scores. |
per |
User-defined percentiles (e.g., per = c(5, 10, 25, 75, 90, 95)). |
by |
The label of the categorical grouping variable (e.g., by="IDCNTRYL") or variables (e.g., by=c("IDCNTRYL", "ITSEX")). |
data |
An R object, normally a data frame, containing the data from intsvy studies. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.per.pv returns a data frame with percentiles and associated standard errors. Default weights (e.g. "TOTWGT" in TIMSS) and percentiles are specified in the config parameter.
See Also
pisa.per.pv, pirls.per.pv, timss.per.pv
Examples
## Not run:
timss.per.pv(pvlabel= paste0("BSMMAT0", 1:5),
per = c(5, 10, 25, 50, 75, 90, 95), by="IDCNTRYL", data=timss8)
intsvy.per.pv(pvnames= paste0("BSMMAT0", 1:5), by="IDCNTRYL",
data=timss8, config=timss8_conf)
pirls.per.pv(pvlabel= paste0("ASRREA0", 1:5), by="IDCNTRYL", data=pirls)
intsvy.per.pv(pvnames= paste0("ASRREA0", 1:5),
per = c(5, 10, 25, 50, 75, 90, 95), by="IDCNTRYL", data=pirls,
config=pirls_conf)
pisa.per.pv(pvlabel= paste0("PV",1:10,"MATH"),
per=c(10, 25, 75, 90), by="CNT", data=pisa)
intsvy.per.pv(pvnames= paste0("PV",1:10,"MATH"),
by="CNT", data=pisa, config=pisa_conf)
## End(Not run)
Regression analysis without plausible values
Description
intsvy.reg performs linear regression analysis (OLS) for an observed depedent variable (NOT for plausible values)
Usage
intsvy.reg(y, x, by, data, export = FALSE, name = "output", folder = getwd(),
config)
Arguments
y |
Label for dependent variable. |
x |
Data labels of independent variables. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNTRYID"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.reg returns a data frame with coefficients, standard errors and t-values. If "by" is specified, results are reported in a list. If the "by" argument is set, then the returning object is of the class "intsvy.reg" with overloaded function plot().
See Also
pisa.reg, pirls.reg, timss.reg
Examples
## Not run:
# install pbiecek/PIAAC package from github to have access to piaac data
piaac.reg(y="AGE_R", x="GENDER_R", by="CNTRYID", data=piaac)
## End(Not run)Regression analysis with plausible values
Description
intsvy.reg.pv performs linear regression analysis (OLS) with plausible values and replicate weights.
Usage
intsvy.reg.pv(x, pvnames, by,
data, std=FALSE, export = FALSE, name = "output", folder = getwd(), config)
Arguments
pvnames |
The names of columns corresponding to the achievement plausible scores. |
x |
Data labels of independent variables. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from TIMSS. |
std |
A logical value. If TRUE standardised regression coefficients are calculated. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.reg.pv prints a data.frame with regression results (i.e., coefficients, standard errors, t-values, R-squared) and stores different regression output including residuals, replicate coefficients, variance within and between, and the regression data.frame in a list object of class "intsvy.reg".
See Also
piaac.reg.pv, pirls.reg.pv, pisa.reg.pv, timss.reg.pv
Examples
## Not run:
intsvy.reg.pv(pvnames=paste0("PV",1:10,"MATH") , x="ST04Q01",
by = "IDCNTRYL",data=pisa, config=pisa_conf)
intsvy.reg.pv(pvnames=paste0("PVLIT", 1:10), x="GENDER_R", by = "CNTRYID",
data=piaac, config=piaac_conf)
intsvy.reg.pv(pvnames=paste0("BSMMAT0", 1:5), by="IDCNTRYL", x="ITSEX",
data=timss8g, config=timss8_conf)
intsvy.reg.pv(pvnames=paste0("ASRREA0", 1:5), by="IDCNTRYL", x="ITSEX",
data=pirls, config=pirls_conf)
## End(Not run)
Correlation matrix
Description
intsvy.rho produces a correlation matrix for observed variables (NOT for plausible values)
Usage
intsvy.rho(variables, by, data,
export = FALSE, name = "output", folder = getwd(), config)
Arguments
variables |
Data labels for the variables in the correlation matrix (e.g., variables=c("ASRREA01", "ASDAGE") ) |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.rho returns a matrix including correlation and standard error values.
See Also
timss.rho, pirls.rho.pv, timss.rho.pv
Examples
## Not run:
pirls.rho(variables=c("ASRREA01", "ASDAGE"), by="IDCNTRYL", data=pirls)
## End(Not run)
Two-way weighted correlation with plausible values
Description
intsvy.rho.pv calculates the correlation and standard error among two achievement variables each based on 5 plausible values or one achievement variable and an observed variable (i.e., with observed scores rather than plausible values).
Usage
intsvy.rho.pv(variable, pvnames, by, data, export=FALSE,
name= "output", folder=getwd(), config)
Arguments
variable |
A data label for the observed variable |
pvnames |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.rho returns a matrix including correlation and standard error values.
See Also
timss.rho, pirls.rho.pv, timss.rho.pv
Examples
## Not run:
timss.rho.pv(variable="BSDGEDUP", pvlabel=paste0("BSMMAT0", 1:5), by="IDCNTRYL", data=timss)
## End(Not run)
Select and merge data
Description
intsvy.select.merge selects and merges data from different international assessment studies. It was developed and it is particularly handy for importing IEA data since original files are organised by instrument, country, grade, etc., in a large number of files. Achievement and weight variabels (all of them) are selected by default.
Usage
intsvy.select.merge(folder = getwd(), countries, student = c(), home,
school, teacher, config)
Arguments
folder |
Directory path where the data are located. The data could be organised within folders but duplicated files should be avoided. |
countries |
The selected countries, supplied with the abbreviation (e.g., countries=c("AUT", "BGR") or codes (countries=c(40, 100)). If no countries are selected, all are selected. |
student |
The data labels for the selected student variables. |
home |
The data labels for the selected home background variables. |
school |
The data labels for the selected school variables. |
teacher |
The data labels for the selected teacher data. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.select.merge returns a data frame with the selected data from study defined in config file.
See Also
timssg4.select.merge, timssg8.select.merge, pisa.select.merge
Examples
## Not run:
pirls <- intsvy.select.merge(folder= getwd(),
countries= c("AUS", "AUT", "AZE", "BFR"),
student= c("ITSEX", "ASDAGE", "ASBGSMR"),
home= c("ASDHEDUP", "ASDHOCCP", "ASDHELA", "ASBHELA"),
school= c("ACDGDAS", "ACDGCMP", "ACDG03"),
config = pirls_conf)
pirls <- intsvy.select.merge(folder= getwd(),
countries= c(36, 40, 31, 957),
student= c("ITSEX", "ASDAGE", "ASBGSMR"),
home= c("ASDHEDUP", "ASDHOCCP", "ASDHELA", "ASBHELA"),
school= c("ACDGDAS", "ACDGCMP", "ACDG03"),
config = pirls_conf)
timss8g <- intsvy.select.merge(folder= getwd(),
countries=c("AUS", "BHR", "ARM", "CHL"),
student =c("BSDGEDUP", "ITSEX", "BSDAGE", "BSBGSLM", "BSDGSLM"),
school=c("BCBGDAS", "BCDG03"), config = timss8_conf)
icils <- intsvy.select.merge(folder= getwd(),
countries=c("AUS", "POL", "SVK"),
student =c("S_SEX", "S_TLANG", "S_MISEI"),
school =c("IP1G02J", "IP1G03A"),
config = icils_conf)
pisa <- pisa.select.merge(folder= getwd(),
school.file="INT_SCQ12_DEC03.sav",
student.file="INT_STU12_DEC03.sav",
student= c("ST01Q01", "ST04Q01", "ESCS", "PARED"),
school = c("CLSIZE", "TCSHORT"),
countries = c("HKG", "USA", "SWE", "POL", "PER"))
## End(Not run)
Frequency table
Description
intsvy.table produces a frequency table for a categorical variable printing percentages and standard errors.
Usage
intsvy.table(variable, by, data, config)
Arguments
variable |
The data label with the variable to be analysed. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PISA. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.table returns a data frame with percentages and standard errors.
See Also
timss.table, pirls.table
Examples
## Not run:
intsvy.table(variable="ASDGSLM", by="IDCNTRYL", data=timss4,
config = intsvy:::timss_conf)
intsvy.table(variable="ST08Q01", by="CNT", data=pisa, config=pisa_conf)
## End(Not run)
Data labels
Description
intsvy.var.labels prints and saves variable labels and names of participating countries in a text file. The function is called by timssg4.var.label, timssg8.var.label, pirls.var.label and pisa.var.label.
Usage
intsvy.var.label(folder = getwd(), name = "Variable labels", output = getwd(),
config)
Arguments
folder |
Directory path where the data files are located. The data could be organized within folders but duplicated files should be avoided. It is assumed that data is in 'sav' files. For TIMSS, PIRLS and ICILS studies the data can be downloaded from |
name |
Name of the output file. |
output |
Folder where the output file is located. |
config |
Object with configuration of a given study. Should contain the slot 'prefixes' with prefixes of filenames with the student, home, school, and teacher data. |
Value
intsvy.var.label returns a list with variable labels for the student, home, school, and teacher data (if applied).
See Also
timssg4.var.label, timssg8.var.label, pirls.var.label, pisa.var.label
Examples
## Not run:
intsvy.var.label(folder= getwd(), config = pirls_conf)
intsvy.var.label(folder= getwd(), config = timss8_conf)
intsvy.var.label(folder= getwd(), config = icils_conf)
intsvy.var.label(folder= getwd(), config = piaac_conf)
## End(Not run)
Utility function
Description
Looks for value labels in data
Usage
is.vlabeled(x)
Arguments
x |
An element from a list |
Details
A utility function for PISA data importation
Value
is.vlabeled returns a vector/list element with logical values
Author(s)
Martin Elff
See Also
adj.measlev, is.vlabeled
Examples
## Not run:
## input of adj.measlev
is.labeled(myvector)
## End(Not run)
PIAAC proficiency levels
Description
Calculates percentage of population at each proficiency level defined by PIAAC. Or at proficiency levels provided by the user.
Usage
piaac.ben.pv(pvlabel, by, data, cutoff, atlevel, export=FALSE,
name= "output", folder=getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNTRYID"), but could be any other categorical variable. |
cutoff |
The cut-off points for the assessment benchmarks (e.g., cutoff= c(357.77, 420.07, 482.38, 544.68, 606.99, 669.30)). |
data |
An R object, normally a data frame, containing the data from PIAAC. |
atlevel |
A logical value. If TRUE, percentages at each level are calculated. Otherwise (FALSE), percentages at or above levels are reported. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
piaac.ben.pv returns a data frame with the percentage of students at each proficiency level and its corresponding standard error.
The total weight, "TOTWGT" and the cut-off points or benchmarks are defined in the config object.
See Also
timss.ben.pv, pirls.ben.pv, pisa.ben.pv
Examples
## Not run:
#Table A2.5
#Percentage of adults scoring at each proficiency level in numeracy
piaac.ben.pv(pvlabel= paste0("PVNUM", 1:10), by="CNTRYID", data=piaac)
#Table A2.1
#Percentage of adults scoring at each proficiency level in literacy
piaac.ben.pv(pvlabel= paste0("PVLIT", 1:10), by="CNTRYID", data=piaac)
## End(Not run)
Calculates mean of variable in PIAAC data
Description
Calculates the mean of an observed variable (NOT one with plausible values) and its standard error.
Usage
piaac.mean(variable, by, data, export = FALSE,
name = "output", folder = getwd())
Arguments
variable |
The label corresponding to the observed variable, for example, "AGE_R" for age of respondent. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNTRYID"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIAAC. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
piaac.mean returns a data frame with means and standard errors.
See Also
pisa.mean, timss.mean, pirls.mean
Examples
## Not run:
# install pbiecek/PIAAC package from github to have access to piaac data
piaac.mean(variable="AGE_R", by="CNTRYID", data=piaac)
## End(Not run)
Calculates mean achievement score for PIAAC data
Description
piaac.mean.pv uses ten plausible values to calculate the mean achievement score and its standard error
Usage
piaac.mean.pv(pvlabel, by, data, export = FALSE, name = "output", folder = getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNTRYID"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIAAC. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
piaac.mean.pv returns a data frame with the mean values and standard errors.
See Also
pisa.mean.pv, timss.mean.pv, pirls.mean.pv
Examples
## Not run:
# install pbiecek/PIAAC package from github to have access to piaac data
piaac.mean.pv(pvlabel = paste0("PVLIT", 1:10), by = "CNTRYID", data = piaac)
piaac.mean.pv(pvlabel = paste0("PVNUM", 1:10), by=c("CNTRYID", "GENDER_R"), data=piaac)
## End(Not run)
Regression analysis for PIAAC
Description
piaac.reg performs linear regression analysis (OLS) for an observed depedent variable (NOT for plausible values)
Usage
piaac.reg(y, x, by, data, export = FALSE, name = "output", folder = getwd())
Arguments
y |
Label for dependent variable. |
x |
Data labels of independent variables. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNTRYID"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIAAC. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
piaac.reg returns a data frame with coefficients, standard errors and t-values. If "by" is specified, results are reported in a list. If the "by" argument is set, then the returning object is of the class "intsvy.reg" with overloaded function plot().
See Also
pisa.reg, pirls.reg, timss.reg
Examples
## Not run:
# install pbiecek/PIAAC package from github to have access to piaac data
piaac.reg(y="AGE_R", x="GENDER_R", by="CNTRYID", data=piaac)
## End(Not run)Regression analysis with plausible values for PIAAC
Description
piaac.reg.pv performs linear regression analysis (OLS) with plausible values and replicate weights.
Usage
piaac.reg.pv(x, pvlabel, by, data,
export = FALSE, name = "output", std=FALSE, folder = getwd())
Arguments
x |
Data labels of independent variables. |
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNTRYID"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIAAC. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
std |
A logical value. If TRUE standardised regression coefficients are calculated. |
folder |
The folder where the exported file is located. |
Value
piaac.reg.pv returns a data frame with coefficients, standard errors and t-values. If "by" is specified, results are reported in a list. If the "by" argument is set, then the returning object is of the class "intsvy.reg" with overloaded function plot().
See Also
pisa.reg.pv, timss.reg.pv, pirls.reg.pv
Examples
## Not run:
# install pbiecek/PIAAC package from github to have access to piaac data
piaac.reg.pv(pvlabel=paste0("PVLIT", 1:10), x="GENDER_R", by = "CNTRYID", data=piaac)
## End(Not run)
Frequency table
Description
piaac.table produces a frequency table for a categorical variable printing percentages and standard errors.
Usage
piaac.table(variable, by, data, export = FALSE, name = "output", folder = getwd())
Arguments
variable |
The data label with the variable to be analysed. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNTRYID"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIAAC. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
piaac.table returns a data frame with percentages and standard errors.
See Also
pisa.table, timss.table, pirls.table
Examples
## Not run:
# install pbiecek/PIAAC package from github to have access to piaac data
piaac.table(variable="I_Q06A", by="CNTRYID", data=piaac)
piaac.table(variable="GENDER_R", by="CNTRYID", data=piaac)
## End(Not run)
PIRLS international benchmarks
Description
pirls.ben.pv calculates the percentage of students performing at or above the cut-off points (scores) given by the useR. The default are the benchmarks established by PIRLS/TIMSS.
Usage
pirls.ben.pv(pvlabel, by, cutoff, data, atlevel=FALSE,
export = FALSE, name = "output", folder = getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
cutoff |
The cut-off points for the assessment benchmarks (e.g., cutoff = c(400, 475, 550, 625). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
atlevel |
A logical value. If TRUE, percentages at each level are calculated. Otherwise (FALSE), percentages at or above levels are reported. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.ben.pv returns a data frame with the percentage of students at or above the benchmark and the corresponding standard error.
The total weight, "TOTWGT" and the cut-off points or benchmarks are defined in the config object.
See Also
timss.ben.pv, pisa.ben.pv
Examples
## Not run:
pirls.ben.pv(pvlabel= paste0("ASRREA0", 1:5), by="IDCNTRYL", data=pirls)
## End(Not run)
Logistic regression analysis
Description
pirls.log performs logistic regression analysis for an observed depedent variable (NOT for plausible values)
Usage
pirls.log(y, x, by, data, export = FALSE,
name = "output", folder = getwd())
Arguments
y |
Label for dependent variable |
x |
Data labels of independent variables (e.g., x = c("ASDHEHLA", "ITSEX") ). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.log prints a data frame with coefficients, standard errors, t-values, and odds ratios. Results are stored in a list object of class "intsvy.reg".
See Also
timss.log, pisa.log
Examples
## Not run:
pisa$SKIP[!(pisa$ST09Q01 =="None" & pisa$ST115Q01 == "None")] <- 1
pisa$SKIP[pisa$ST09Q01 =="None" & pisa$ST115Q01 == "None"] <- 0
pisa$LATE[!pisa$ST08Q01=="None"] <- 1
pisa$LATE[pisa$ST08Q01=="None"] <- 0
pisa.log(y="SKIP", x="LATE", by="IDCNTRYL", data = pisa)
## End(Not run)Logistic regression analysis with plausible values
Description
pirls.log.pv performs logistic regression with plausible values and replicate weights.
Usage
pirls.log.pv(pvlabel, x, cutoff, by,
data, export=FALSE, name= "output", folder=getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
x |
Data labels of independent variables. |
cutoff |
The cut-off point at which the dependent plausible values scores are dichotomised (1 is larger than the cut-off) |
by |
The label for the categorical grouping variable (i.e., by="IDCNTRYL") or variables (e.g., x= c("IDCNTRYL", "ITSEX")). |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.log.pv returns a data frame with coefficients, standard errors, t-values, and odds ratios. If "by" is specified, results are reported in a list.
See Also
pisa.log.pv, timss.log.pv
Examples
## Not run:
timss.log.pv(pvlabel="paste0("BSMMAT0", 1:5), cutoff= 550,
x=c("ITSEX", "BSBGSLM"), by="IDCNTRYL", data=timss8g)
intsvy.log.pv(pvlabel=paste0("BSMMAT0", 1:5), cutoff= 550,
x="ITSEX", by="IDCNTRYL", data=timss8g, config=timss8_conf)
## End(Not run)Calculates mean of variable
Description
Calculates the mean of an observed variable (NOT one with plausible values) and its standard error.
Usage
pirls.mean(variable, by, data,
export = FALSE, name = "output", folder = getwd())
Arguments
variable |
The label corresponding to the observed variable, for example, "ASDAGE", for the age of the student. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.mean returns a data frame with means and standard errors.
See Also
timss.mean, pisa.mean
Examples
## Not run:
pirls.mean(variable='ASBHELA', by= 'IDCNTRYL', data=pirls)
## End(Not run)
Calculates mean achievement score
Description
pirls.mean.pv uses five plausible values to calculate the mean achievement score and its standard error
Usage
pirls.mean.pv(pvlabel, by,
data, export = FALSE, name = "output", folder = getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores, for example, paste0("ASRREA0", 1:5). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.mean.pv returns a data frame with the mean values and standard errors.
See Also
timss.mean.pv, pisa.mean.pv
Examples
## Not run:
pirls.mean.pv(pvlabel= paste0("ASRREA0", 1:5), by= "IDCNTRYL", data=pirls)
pirls.mean.pv(pvlabel= paste0("ASRREA0", 1:5), by= c("IDCNTRYL", "ITSEX"), data=pirls)
## End(Not run)
PIRLS percentiles
Description
Calculates percentiles for plausible values
Usage
pirls.per.pv(pvlabel, by, per, data, export=FALSE,
name= "output", folder=getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
per |
User-defined percentiles (e.g., per = c(5, 10, 25, 75, 90, 95)). |
by |
The label of the categorical grouping variable (e.g., by="IDCNTRYL") or variables (e.g., by=c("IDCNTRYL", "ITSEX")). |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.per.pv returns a data frame with percentiles and associated standard errors. Default weights (e.g. "TOTWGT" in TIMSS) and percentiles are specified in the config parameter.
See Also
pisa.per.pv, timss.per.pv
Examples
## Not run:
pirls.per.pv(pvlabel=paste0("ASRREA0", 1:5),
per = c(5, 10, 25, 50, 75, 90, 95), by="IDCNTRYL", data=pirls)
## End(Not run)
Regression analysis
Description
pirls.reg performs linear regression analysis (OLS) for an observed depedent variable (NOT for plausible values)
Usage
pirls.reg(y, x, by, data, export = FALSE,
name = "output", folder = getwd())
Arguments
y |
Label for dependent variable |
x |
Data labels of independent variables (e.g., x = c("ASDHEHLA", "ITSEX") ). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.reg prints a data.frame with regression results (i.e., coefficients, standard errors, t-values, R-squared) and stores different regression output including residuals and replicate coefficients in a list object of class "intsvy.reg".
See Also
timss.reg
Examples
## Not run:
# Recode ASBGBOOK
table(as.numeric(pirls$ASBGBOOK), pirls$ASBGBOOK)
pirls$BOOK[as.numeric(pirls$ASBGBOOK)==1] <- 5
pirls$BOOK[as.numeric(pirls$ASBGBOOK)==2] <- 18
pirls$BOOK[as.numeric(pirls$ASBGBOOK)==3] <- 63
pirls$BOOK[as.numeric(pirls$ASBGBOOK)==4] <- 151
pirls$BOOK[as.numeric(pirls$ASBGBOOK)==5] <- 251
table(pirls$BOOK)
pirls.reg(y= "BOOK", x= "ITSEX", by="IDCNTRYL", data=pirls)
## End(Not run)
Regression analysis with plausible values
Description
pirls.reg.pv performs linear regression analysis (OLS) with plausible values and replicate weights.
Usage
pirls.reg.pv(x, pvlabel, by,
data, std=FALSE, export = FALSE, name = "output", folder = getwd())
Arguments
x |
Data labels of independent variables (e.g., x = c("ASDHEHLA", "ITSEX") ). |
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
std |
A logical value. If TRUE standardised regression coefficients are calculated. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.reg.pv prints a data.frame with regression results (i.e., coefficients, standard errors, t-values, R-squared) and stores different regression output including residuals, replicate coefficients, variance within and between, and the regression data.frame in a list object of class "intsvy.reg".
See Also
timss.reg.pv, pisa.reg.pv
Examples
## Not run:
pirls$SEX[pirls$ITSEX=="BOY"]=1
pirls$SEX[pirls$ITSEX=="GIRL"]=0
pirls.reg.pv(pvlabel= paste0("ASRREA0", 1:5), by="IDCNTRYL", x="SEX", data=pirls)
## End(Not run)
Correlation matrix
Description
pirls.rho produces a correlation matrix for observed variables (NOT for plausible values)
Usage
pirls.rho(variables, by, data,
export = FALSE, name = "output", folder = getwd())
Arguments
variables |
Data labels for the variables in the correlation matrix (e.g., variables=c("ASRREA01", "ASDAGE") ) |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.rho returns a matrix including correlation and standard error values.
See Also
timss.rho, pirls.rho.pv, timss.rho.pv
Examples
## Not run:
pirls.rho(variables=c("ASRREA01", "ASDAGE"), by="IDCNTRYL", data=pirls)
## End(Not run)
Two-way weighted correlation with plausible values
Description
pirls.rho.pv calculates the correlation and standard error among two achievement variables each based on 5 plausible values or one achievement variable and an observed variable (i.e., with observed scores rather than plausible values).
Usage
pirls.rho.pv(variable, pvlabel, by,
data, export = FALSE, name = "output", folder = getwd())
Arguments
variable |
A data label for the observed variable (e.g., variable="ASDAGE") |
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.rho.pv returns a matrix with correlations and standard errors.
See Also
timss.rho.pv, pirls.rho, timss.rho
Examples
## Not run:
pirls.rho.pv(variable="BSDGEDUP", pvlabel=paste0("BSMMAT0", 1:5), by="IDCNTRYL", data=timss)
## End(Not run)
Select and merge data
Description
pirls.select.merge selects and merges data from PIRLS. Achievement and weight variabels (all of them) are selected by default.
Usage
pirls.select.merge(folder = getwd(), countries, student = c(),
home, school, teacher)
Arguments
folder |
Directory path where the data are located. The data could be organized within folders but it should not be duplicated. |
countries |
The selected countries, supplied with the abbreviation (e.g., countries=c("AUT", "BGR") or codes (countries=c(40, 100)). If no countries are selected, all are selected. |
student |
The data labels for the selected student variables. |
home |
The data labels for the selected home background variables. |
school |
The data labels for the selected school variables. |
teacher |
The data labels for the selected teacher data. |
Value
pirls.select.merge returns a data frame with the selected data from PIRLS.
See Also
timssg4.select.merge, timssg8.select.merge, pisa.select.merge
Examples
## Not run:
pirls <- pirls.select.merge(folder= getwd(),
countries= c(36, 40, 31, 957),
student= c("ITSEX", "ASDAGE", "ASBGSMR"),
home= c("ASDHEDUP", "ASDHOCCP", "ASDHELA", "ASBHELA"),
school= c("ACDGDAS", "ACDGCMP", "ACDG03"))
## End(Not run)
Frequency table
Description
pirls.table produces a frequency table for a categorical variable printing percentages and standard errors. Information about weight is extracted from intsvy:::pirls_conf.
Usage
pirls.table(variable, by, data,
export = FALSE, name = "output", folder = getwd())
Arguments
variable |
The data label with the variable to be analysed. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pirls.table returns a data frame with percentages and standard errors.
See Also
timss.table, pisa.table
Examples
## Not run:
pirls.table(variable="ASDHELA", by="IDCNTRYL", data=pirls)
## End(Not run)Data labels
Description
pirls.var.labels prints and saves variable labels and names of participating countries in a text file
Usage
pirls.var.label(folder = getwd(), name = "Variable labels", output = getwd())
Arguments
folder |
Directory path where the PIRLS data are located. The data could be organized within folders but it should not be duplicated. |
name |
Name of output file. |
output |
Folder where output file is located. |
Value
pirls.var.label returns a list with variable labels for the student, home, school, and teacher data.
See Also
timssg4.var.label, timssg8.var.label, pisa.var.label
Examples
## Not run:
pirls.var.label(folder= getwd())
## End(Not run)
PISA proficiency levels
Description
Calculates percentage of students at each proficiency level defined by PISA. Or at proficiency levels provided by the useR.
Usage
pisa.ben.pv(pvlabel, by, cutoff, data, atlevel=FALSE,
export=FALSE, name= "output", folder=getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
cutoff |
The cut-off points for the assessment benchmarks (e.g., cutoff= c(357.77, 420.07, 482.38, 544.68, 606.99, 669.30)). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PISA. |
atlevel |
A logical value. If TRUE, percentages at each level are calculated. Otherwise (FALSE), percentages at or above levels are reported. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.ben.pv returns a data frame with the percentage of students at each proficiency level and its corresponding standard error.
The total weight, "TOTWGT" and the cut-off points or benchmarks are defined in the config object.
See Also
timss.ben.pv, pirls.ben.pv
Examples
## Not run:
pisa.ben.pv(pvlabel= paste0("PV",1:10,"MATH"), by="IDCNTRYL", atlevel=TRUE, data=pisa)
## End(Not run)
Logistic regression analysis
Description
pisa.log performs logistic regression analysis (OLS) for an observed depedent variable (NOT for plausible values)
Usage
pisa.log(y, x, by, data, export=FALSE, name= "output", folder=getwd())
Arguments
y |
Label for dependent variable. |
x |
Data labels of independent variables. |
by |
The label for the grouping variable, usually the countries (i.e., by="CNT"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PISA. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.log prints a data.frame with regression results (i.e., coefficients, standard errors, t-values, R-squared) and stores replicate estimates and other regression output in a list object of class "intsvy.reg".
See Also
pirls.log, timss.log
Examples
## Not run:
pisa$SKIP[!(pisa$ST09Q01 =="None" & pisa$ST115Q01 == "None")] <- 1
pisa$SKIP[pisa$ST09Q01 =="None" & pisa$ST115Q01 == "None"] <- 0
pisa$LATE[!pisa$ST08Q01=="None"] <- 1
pisa$LATE[pisa$ST08Q01=="None"] <- 0
pisa.log(y="SKIP", x="LATE", by="IDCNTRYL", data = pisa)
## End(Not run)Logistic regression analysis with plausible values
Description
pisa.log.pv performs logistic regression with plausible values and replicate weights.
Usage
pisa.log.pv(pvlabel, x, by, cutoff,
data, export=FALSE, name= "output", folder=getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
x |
Data labels of independent variables. |
cutoff |
The cut-off point at which the dependent plausible values scores are dichotomised (1 is larger than the cut-off) |
by |
The label for the categorical grouping variable (i.e., by="IDCNTRYL") or variables (e.g., x= c("IDCNTRYL", "ST79Q03")). |
data |
An R object, normally a data frame, containing the data from PISA. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.log.pv returns a data frame with coefficients, standard errors, t-values, and odds ratios. If "by" is specified, results are reported in a list.
See Also
timss.log.pv, pirls.log.pv
Examples
## Not run:
timss.log.pv(pvlabel=paste0("BSMMAT0", 1:5), cutoff= 550,
x=c("ITSEX", "BSBGSLM"), by="IDCNTRYL", data=timss8g)
intsvy.log.pv(pvlabel=paste0("BSMMAT0", 1:5), cutoff= 550, x="ITSEX",
by="IDCNTRYL", data=timss8g, config=timss8_conf)
## End(Not run)Calculates mean of variable
Description
Calculates the mean of an observed variable (NOT one with plausible values) and its standard error.
Usage
pisa.mean(variable, by, data, export = FALSE,
name = "output", folder = getwd())
Arguments
variable |
The label corresponding to the observed variable, for example, ""ESCS"", for the student SES. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PISA. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.mean returns a data frame with means and standard errors.
See Also
timss.mean, pirls.mean, piaac.mean
Examples
## Not run:
pisa.mean(variable="ESCS", by="IDCNTRYL", data=pisa)
pisa.mean(variable="PARED", by="IDCNTRYL", data=pisa)
pisa.mean(variable="BELONG", by="IDCNTRYL", data=pisa)
pisa.mean(variable="BELONG", by=c("IDCNTRYL", "ST04Q01"), data=pisa)
## End(Not run)
Calculates mean achievement score
Description
pisa.mean.pv uses five plausible values to calculate the mean achievement score and its standard error
Usage
pisa.mean.pv(pvlabel, by, data, export = FALSE, name = "output",
folder = getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores, for example, paste0("PV",1:10,"MATH"). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.mean.pv returns a data frame with the mean values and standard errors.
See Also
timss.mean.pv, pirls.mean.pv, piaac.mean.pv
Examples
## Not run:
pisa.mean.pv(pvlabel = paste0("PV",1:10,"MATH"), by = "IDCNTRYL", data = pisa)
pisa.mean.pv(pvlabel = paste0("PV",1:10,"MATH"), by = c("IDCNTRYL", "ST04Q01"), data = pisa)
pisa.mean.pv(pvlabel = "paste0("PV",1:10,"MATH"), by = "IDCNTRYL", data = pisa)
## End(Not run)
PISA percentiles
Description
Calculates percentiles for plausible values.
Usage
pisa.per.pv(pvlabel, by, per, data, export=FALSE, name= "output",
folder=getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
per |
User-defined percentiles (e.g., per = c(5, 10, 25, 75, 90, 95)). |
by |
The label of the categorical grouping variable (e.g., by="IDCNTRYL") or variables (e.g., by=c("IDCNTRYL", "ST79Q03")). |
data |
An R object, normally a data frame, containing the data from PISA. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.per.pv returns a data frame with percentiles and associated standard errors. Default weights (e.g. "TOTWGT" in TIMSS) and percentiles are specified in the config parameter.
See Also
timss.per.pv, pirls.per.pv
Examples
## Not run:
pisa.per.pv(pvlabel=paste0("PV",1:10,"MATH"), per=c(10, 25, 75, 90), by="IDCNTRYL", data=pisa)
## End(Not run)
Regression analysis
Description
pisa.reg performs linear regression analysis (OLS) for an observed depedent variable (NOT for plausible values)
Usage
pisa.reg(y, x, by, data, export = FALSE, name = "output", folder = getwd())
Arguments
y |
Label for dependent variable. |
x |
Data labels of independent variables. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PISA. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.reg prints a data.frame with regression results (i.e., coefficients, standard errors, t-values, R-squared) and stores different regression output including residuals and replicate coefficients in a list object of class "intsvy.reg".
See Also
pirls.reg, timss.reg, piaac.reg
Examples
## Not run:
pisa.reg(y="BELONG", x="ST04Q01", by="IDCNTRYL", data=pisa)
## End(Not run)Regression analysis with plausible values
Description
pisa.reg.pv performs linear regression analysis (OLS) with plausible values and replicate weights.
Usage
pisa.reg.pv(x, pvlabel, by, data,
export = FALSE, name = "output", folder = getwd(), std=FALSE)
Arguments
x |
Data labels of independent variables. |
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PISA. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
std |
A logical value. If TRUE standardised regression coefficients are calculated. |
Value
pisa.reg.pv prints a data.frame with regression results (i.e., coefficients, standard errors, t-values, R-squared) and stores different regression output including residuals, replicate coefficients, variance within and between, and the regression data.frame in a list object of class "intsvy.reg".
See Also
timss.reg.pv, pirls.reg.pv, piaac.reg.pv
Examples
## Not run:
pisa.reg.pv(pvlabel=paste0("PV",1:10,"MATH"), x="ST04Q01", by = "IDCNTRYL", data=pisa)
## End(Not run)
Correlation matrix
Description
pisa.rho produces a correlation matrix for observed variables (NOT for plausible values)
Usage
pisa.rho(variables, by, data, export=FALSE, name= "output", folder=getwd())
Arguments
variables |
Data labels for the variables in the correlation matrix (e.g., variables=c("TCHBEHTD", "TCHBEHSO")) |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PISA. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.rho returns a matrix including correlation and standard error values.
See Also
timss.rho, pirls.rho, pirls.rho.pv, timss.rho.pv
Examples
## Not run:
pisa.rho(variables=c("COGACT", "TCHBEHTD", "TCHBEHSO", "CLSMAN" ), by="IDCNTRYL", data=pisa)
## End(Not run)
Select and merge data
Description
pisa.select.merge selects and merges data from PISA. Achievement and weight variables (all of them) are selected by default.
Usage
pisa.select.merge(folder=getwd(), student.file, parent.file=c(), school.file=c(),
countries, student=c(), parent, school)
Arguments
folder |
Directory path where the PISA data are located, if all the data are located in the same folder. |
student.file |
Student file name if 'folder' is provided, otherwise full path name of student dataset (required argument). |
parent.file |
Parent file name if 'folder' is provided, otherwise full path name of parent dataset. |
school.file |
School file name if 'folder' is provided, otherwise full path name of school dataset. |
countries |
The selected countries, supplied with the abbreviation (e.g., countries=c("DEU", "NOR") or codes. If no countries are selected, all are selected. |
student |
The data labels for the selected student variables. |
parent |
The data labels for the selected parental variables. |
school |
The data labels for the selected school variables. |
Value
pisa.select.merge returns a data frame with the selected data from PISA.
See Also
timssg4.select.merge, timssg8.select.merge, pirls.select.merge
Examples
## Not run:
pisa <- pisa.select.merge(folder=getwd(),
school.file="INT_SCQ12_DEC03.sav",
student.file="INT_STU12_DEC03.sav",
parent.file="INT_PAQ12_DEC03.sav",
student= c("IMMIG", "ESCS", "ST04Q01", "ST61Q04", "ST62Q01", "ST08Q01"),
parent = c("PARINVOL", "PARSUPP"),
school = c("STRATIO", "SCHAUTON", "CLSIZE"),
countries = c("HKG", "USA", "SWE", "POL", "PER"))
## End(Not run)
Frequency table
Description
pisa.table produces a frequency table for a categorical variable printing percentages and standard errors.
Usage
pisa.table(variable, by, data, export = FALSE, name = "output", folder = getwd())
Arguments
variable |
The data label with the variable to be analysed. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PISA. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
pisa.table returns a data frame with percentages and standard errors.
See Also
timss.table, pirls.table
Examples
## Not run:
pisa.table(variable="ST01Q01", by="IDCNTRYL", data=pisa)
pisa.table(variable="ST08Q01", by="IDCNTRYL", data=pisa)
## End(Not run)
Data labels
Description
pisa.var.labels prints and saves variable labels and names of participating countries in a text file
Usage
pisa.var.label(folder=getwd(), student.file, parent.file=c(), school.file=c(),
name="Variable labels", output=getwd())
Arguments
folder |
Directory path where the PISA data are located, if all the data are located in the same folder. |
student.file |
Student file name if 'folder' is provided, otherwise full path name of student dataset (required argument). |
parent.file |
Parent file name if 'folder' is provided, otherwise full path name of parent dataset. |
school.file |
School file name if 'folder' is provided, otherwise full path name of school dataset. |
name |
Name of output file. |
output |
Folder where output file is located. |
Value
pisa.var.label returns a list with variable labels for the student, parent, and school data.
See Also
timssg4.var.label, timssg8.var.label, pirls.var.label
Examples
## Not run:
pisa.var.label(folder=getwd(), school.file="INT_SCQ12_DEC03.sav",
student.file="INT_STU12_DEC03.sav", parent.file="INT_PAQ12_DEC03.sav")
## End(Not run)
Graphical representation of means in groups
Description
Functions pisa.mean, pisa.mean.pv, piaac.mean, piaac.mean.pv produce object of the class intsvy.mean. The function plot.intsvy.mean presents these means graphically.
Usage
## S3 method for class 'intsvy.mean'
plot(x, se = TRUE, sort = FALSE, ...)
Arguments
x |
An object of the class intsvy.mean returned by pisa.mean, pisa.mean.pv, piaac.mean or piaac.mean.pv functions. |
se |
If TRUE add whiskers for standard errors. |
sort |
If TRUE groups are sorted along averages. |
... |
Not used. Required for cran-check. |
Value
Returns object of ggplot class with dotplot. Works for one way, two-way and three-way effects.
See Also
plot.intsvy.table, plot.intsvy.reg
Examples
## Not run:
# Country averages
head(pmeansNC <- piaac.mean.pv(pvlabel="NUM", by="CNTRYID", data=piaac, export=FALSE))
# plotting country average NUM performance
plot(pmeansNC) + ggtitle("Country performance in NUM")
# without se bars, not good idea
plot(pmeansNC, se=FALSE)
# sorted, thats better
plot(pmeansNC, sort=TRUE)
# Country averages for different age groups
head(pmeansNCA <- piaac.mean.pv(pvlabel="NUM", by=c("CNTRYID", "AGEG10LFS"),
data=piaac, export=FALSE))
#
# plotting country average within
# age groups NUM performance
plot(pmeansNCA, sort=TRUE)
# Country averages for different age and gender groups (changed order)
head(pmeansNCGA <- piaac.mean.pv(pvlabel="NUM", by=c("CNTRYID", "GENDER_R", "AGEG10LFS"),
data=piaac, export=FALSE))
#
# plotting country average within
# age and gender groups NUM performance
plot(na.omit(pmeansNCGA), sort=TRUE)
## End(Not run)
Graphical representation of regression models in groups
Description
Functions pisa.reg, pisa.reg.pv, piaac.reg and piaac.reg.pv produce object of the class intsvy.reg. The function plot.intsvy.reg presents this list of regression models graphically.
Usage
## S3 method for class 'intsvy.reg'
plot(x, ..., vars, se = TRUE, sort = FALSE)
Arguments
x |
An object of the class intsvy.reg returned by pisa.reg, pisa.reg.pv, piaac.reg and piaac.reg.pv functions. |
... |
Other arguments |
vars |
Variable labels of coefficients to be plotted. If none selected all coefficients are plotted including the R-squared |
se |
If TRUE add whiskers for standard errors. |
sort |
If TRUE groups are sorted in alphabetical order. |
Value
Returns object of ggplot class with barplot. As with other ggplot objects the plus sign "+" can be used outside this function to modify graph parameters of the returning ggplot object. Works for one way, two-way and three-way contingency tables.
See Also
plot.intsvy.table, plot.intsvy.mean
Examples
## Not run:
# Independent variables
x.vars <- c("ESCS", "COGACT", "TCHBEHTD", "TCHBEHSO")
# Model estimation
my.mod <- pisa.reg.pv(pvlabel="MATH", x=x.vars, by="IDCNTRYL", data=pisa12)
# Plot
plot(gen.mod, vars = c("COGACT", "TCHBEHTD", "TCHBEHSO"), sort=TRUE)
## End(Not run)
Graphical representation of frequency tables
Description
Functions pisa.table and piaac.table produce object of the class intsvy.table. The function plot.intsvy.table presents this table graphically.
Usage
## S3 method for class 'intsvy.table'
plot(x, se=FALSE, stacked=FALSE, centered = FALSE, midpoint = NA, ...)
Arguments
x |
An object of the class intsvy.table returned by pisa.table or piaac.table functions. |
se |
If TRUE add whiskers for standard errors (only for stacked=FALSE). |
stacked |
If TRUE plot bars stacked one over another. |
centered |
If TRUE then bars will be centered around |
midpoint |
A single number, which specifies the segment around which bars are centered. By default it's the middle segment calculated as |
... |
Not used. Required for cran-check. |
Value
Returns object of ggplot class with barplot. Works for one way, two-way and three-way contingency tables.
See Also
plot.intsvy.mean, plot.intsvy.reg
Examples
## Not run:
# install pbiecek/PIAAC package from github to have access to piaac data
# age distribution in whole dataset
(ptable <- piaac.table(variable="AGEG10LFS", data=piaac))
# age distribution in whole dataset
plot(ptable)
plot(ptable, centered=TRUE)
# age distribution within countries
head(ptableC <- piaac.table(variable="AGEG10LFS", by="CNTRYID", data=piaac))
# age distribution within countries
plot(ptableC, stacked=TRUE)
plot(na.omit(ptableC), centered=TRUE)
# age distribution within countries and gender segments
head(ptableCA <- piaac.table(variable="AGEG10LFS", by=c("CNTRYID", "GENDER_R"), data=piaac))
# age distribution within countries and gender segments
plot(na.omit(ptableCA), stacked=TRUE)
plot(na.omit(ptableCA), centered=TRUE)
## End(Not run)
TIMSS international benchmarks
Description
timss.ben.pv calculates the percentage of students performing at or above the cut-off points (scores) given by the useR. The default are the benchmarks established by PIRLS/TIMSS
Usage
timss.ben.pv(pvlabel, by, cutoff, data, atlevel=FALSE,
export = FALSE, name = "output", folder = getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
cutoff |
The cut-off points for the assessment benchmarks (e.g., cutoff = c(400, 475, 550, 625)). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from TIMSS. |
atlevel |
A logical value. If TRUE, percentages at each level are calculated. Otherwise (FALSE), percentages at or above levels are reported. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.ben.pv returns a data frame with the percentage of students at or above the benchmark and the corresponding standard error.
The total weight, "TOTWGT" and the cut-off points or benchmarks are defined in the config object.
See Also
pirls.ben.pv, pisa.ben.pv
Examples
## Not run:
timss.ben.pv(pvlabel= paste0("BSMMAT0", 1:5), by="IDCNTRYL",
cutoff = c(400, 475, 550, 625), data=timss8g)
timss.ben.pv(pvlabel= paste0("BSMMAT0", 1:5), by="IDCNTRYL", data=timss4g)
## End(Not run)
Logistic regression analysis
Description
timss.log performs logistic regression analysis for an observed depedent variable (NOT for plausible values)
Usage
timss.log(y, x, by, data, export = FALSE,
name = "output", folder = getwd())
Arguments
y |
Label for dependent variable |
x |
Data labels of independent variables (e.g., x = c("ASDHEHLA", "ITSEX") ). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from PIRLS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.log prints a data frame with coefficients, standard errors, t-values, and odds ratios. Results are stored in a list object of class "intsvy.reg".
See Also
pirls.log, pisa.log
Examples
## Not run:
pisa$SKIP[!(pisa$ST09Q01 =="None" & pisa$ST115Q01 == "None")] <- 1
pisa$SKIP[pisa$ST09Q01 =="None" & pisa$ST115Q01 == "None"] <- 0
pisa$LATE[!pisa$ST08Q01=="None"] <- 1
pisa$LATE[pisa$ST08Q01=="None"] <- 0
pisa.log(y="SKIP", x="LATE", by="IDCNTRYL", data = pisa)
## End(Not run)Logistic regression analysis with plausible values
Description
timss.log.pv performs logistic regression with plausible values and replicate weights.
Usage
timss.log.pv(pvlabel, x, by, cutoff,
data, export=FALSE, name= "output", folder=getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
x |
Data labels of independent variables. |
cutoff |
The cut-off point at which the dependent plausible values scores are dichotomised (1 is larger than the cut-off) |
by |
The label for the categorical grouping variable (i.e., by="IDCNTRYL") or variables (e.g., x= c("IDCNTRYL", "ITSEX")). |
data |
An R object, normally a data frame, containing the data from TIMSS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.log.pv returns a data frame with coefficients, standard errors, t-values, and odds ratios. If "by" is specified, results are reported in a list.
See Also
pisa.log.pv, pirls.log.pv
Examples
## Not run:
timss.log.pv(pvlabel=paste0("BSMMAT0", 1:5), cutoff= 550,
x=c("ITSEX", "BSBGSLM"), by="IDCNTRYL", data=timss8g)
intsvy.log.pv(pvlabel=paste0("BSMMAT0", 1:5), cutoff= 550, x="ITSEX",
by="IDCNTRYL", data=timss8g, config=timss8_conf)
## End(Not run)Calculates mean of variable
Description
Calculates the mean of an observed variable (NOT one with plausible values) and its standard error.
Usage
timss.mean(variable, by, data,
export = FALSE, name = "output", folder = getwd())
Arguments
variable |
The label corresponding to the observed variable, for example, "ASDAGE", for the age of the student. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from TIMSS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.mean returns a data frame with means and standard errors.
See Also
pirls.mean, pisa.mean
Examples
## Not run:
timss.mean(variable='ASBGSLM', by='IDCNTRYL', data=timss4g)
timss.mean(variable='BSBGSLM', by='IDCNTRYL', data=timss8g)
## End(Not run)
Calculates mean achievement score
Description
timss.mean.pv uses five plausible values to calculate the mean achievement score and its standard error
Usage
timss.mean.pv(pvlabel, by, data,
export = FALSE, name = "output", folder = getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores, for example, paste0("BSMMAT0", 1:5). |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.mean.pv returns a data frame with the mean values and standard errors.
See Also
pirls.mean.pv, pisa.mean.pv
Examples
## Not run:
timss.mean.pv(pvlabel= paste0("BSMMAT0", 1:5), by= "IDCNTRYL", data=timss4g)
timss.mean.pv(pvlabel= paste0("BSMMAT0", 1:5), by= c("IDCNTRYL", "ITSEX"), data=timss8g)
## End(Not run)
TIMSS percentiles
Description
Calculates percentiles for plausible values
Usage
timss.per.pv(pvlabel, by, per, data, export=FALSE, name= "output",
folder=getwd())
Arguments
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
per |
User-defined percentiles (e.g., per = c(5, 10, 25, 75, 90, 95)). |
by |
The label of the categorical grouping variable (e.g., by="IDCNTRYL") or variables (e.g., by=c("IDCNTRYL", "ITSEX")). |
data |
An R object, normally a data frame, containing the data from TIMSS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.per.pv returns a data frame with percentiles and associated standard errors. Default weights (e.g. "TOTWGT" in TIMSS) and percentiles are specified in the config parameter.
See Also
pisa.per.pv, pirls.per.pv
Examples
## Not run:
timss.per.pv(pvlabel=paste0("BSMMAT0", 1:5),
per = c(5, 10, 25, 50, 75, 90, 95), by="IDCNTRYL", data=timssg8)
## End(Not run)
Regression analysis
Description
timss.reg performs linear regression analysis (OLS) for an observed depedent variable (NOT for plausible values)
Usage
timss.reg(y, x, by, data,
export = FALSE, name = "output", folder = getwd())
Arguments
y |
Label for dependent variable. |
x |
Data labels of independent variables. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from TIMSS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.reg prints a data.frame with regression results (i.e., coefficients, standard errors, t-values, R-squared) and stores different regression output including residuals and replicate coefficients in a list object of class "intsvy.reg".
See Also
pirls.reg
Examples
## Not run:
timss.reg(y="BSDAGE", x="ITSEX", by="IDCNTRYL", data=timss8g)
## End(Not run)Regression analysis with plausible values
Description
timss.reg.pv performs linear regression analysis (OLS) with plausible values and replicate weights.
Usage
timss.reg.pv(x, pvlabel, by,
data, std=FALSE, export = FALSE, name = "output", folder = getwd())
Arguments
x |
Data labels of independent variables. |
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from TIMSS. |
std |
A logical value. If TRUE standardised regression coefficients are calculated. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.reg.pv prints a data.frame with regression results (i.e., coefficients, standard errors, t-values, R-squared) and stores different regression output including residuals, replicate coefficients, variance within and between, and the regression data.frame in a list object of class "intsvy.reg".
See Also
pirls.reg.pv, pisa.reg.pv
Examples
## Not run:
timss8g$SEX[timss8g$ITSEX=="BOY"]=1
timss8g$SEX[timss8g$ITSEX=="GIRL"]=0
timss.reg.pv(pvlabel= paste0("BSMMAT0", 1:5), by=c("IDCNTRYL"), x="SEX", data=timss8g)
## End(Not run)
Correlation matrix
Description
timss.rho produces a correlations matrix for observed variables (NOT for plausible values)
Usage
timss.rho(variables, by, data,
export = FALSE, name = "output", folder = getwd())
Arguments
variables |
Data labels for the variables in the correlation matrix. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from TIMSS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.rho returns a matrix including correlation and standard error values.
See Also
pirls.rho, pirls.rho.pv, timss.rho.pv
Examples
## Not run:
timss.rho(variables=c("BSMMAT01", "BSDGEDUP"), data=timss)
## End(Not run)
Two-way weighted correlation with plausible values
Description
timss.rho.pv calculates the correlation and standard error among two achievement variables each based on 5 plausible values or one achievement variable and an observed variable (i.e., with observed scores rather than plausible values).
Usage
timss.rho.pv(variable, pvlabel, by,
data, export = FALSE, name = "output", folder = getwd())
Arguments
variable |
A data label for the observed variable |
pvlabel |
The names of columns corresponding to the achievement plausible scores. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from TIMSS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.rho.pv returns a matrix with correlations and standard errors.
See Also
pirls.rho.pv, pirls.rho, timss.rho
Examples
## Not run:
timss.rho.pv(variable="BSDGEDUP", pvlabel=paste0("BSMMAT0", 1:5), by="IDCNTRYL", data=timss)
## End(Not run)
Frequency table
Description
timss.table produces a frequency table for a categorical variable printing percentages and standard errors. Information about weight is extracted from intsvy:::pirls_conf.
Usage
timss.table(variable, by, data,
export = FALSE, name = "output", folder = getwd())
Arguments
variable |
The data label with the variable to be analysed. |
by |
The label for the grouping variable, usually the countries (i.e., by="IDCNTRYL"), but could be any other categorical variable. |
data |
An R object, normally a data frame, containing the data from TIMSS. |
export |
A logical value. If TRUE, the output is exported to a file in comma-separated value format (.csv) that can be opened from LibreOffice or Excel. |
name |
The name of the exported file. |
folder |
The folder where the exported file is located. |
Value
timss.table returns a data frame with percentages and standard errors.
See Also
pirls.table, pisa.table
Examples
## Not run:
timss.table(variable="ASDGSLM", by="IDCNTRYL", data=timss4g)
timss.table(variable="BSDGSLM", by="IDCNTRYL", data=timss8g)
## End(Not run)
Select and merge data
Description
timssg4.select.merge selects and merges data from TIMSS G4. Achievement and weight variables (all of them) are selected by default.
Usage
timssg4.select.merge(folder = getwd(), countries, student = c(), home, school, teacher)
Arguments
folder |
Directory path where the data are located. The data could be organized within folders but it should not be duplicated. |
countries |
The selected countries, supplied with the abbreviation (e.g., countries=c("AUT", "BGR") or codes (countries=c(40, 100)). If no countries are selected, all are selected. |
student |
The data labels for the selected student variables. |
home |
The data labels for the selected home background variables. |
school |
The data labels for the selected school variables. |
teacher |
The data labels for the selected teacher variables. |
Value
timssg4.select.merge returns a data frame with the selected data from TIMSS G4.
See Also
timssg8.select.merge, pirls.select.merge, pisa.select.merge
Examples
## Not run:
timss4g <- timssg4.select.merge(folder=getwd(),
countries=c("AUS", "BHR", "ARM", "CHL"),
student =c("ITSEX", "ASDAGE", "ASBGSLM", "ASDGSLM"),
home = c("ASDHEDUP", "ASDHENA"),
school =c("ACDG03", "ACDGENS"))
## End(Not run)
Data labels
Description
timssg4.var.labels prints and saves variable labels and names of participating countries in a text file
Usage
timssg4.var.label(folder = getwd(), name = "Variable labels", output = getwd())
Arguments
folder |
Directory path where the TIMSS G4 data are located. The data could be organized within folders but it should not be duplicated. |
name |
Name of output file. |
output |
Folder where output file is located. |
Value
timssg4.var.label returns a list with variable labels for the student, home, school, and teacher data.
See Also
timssg8.var.label, pirls.var.label, pisa.var.label
Examples
## Not run:
timssg4.var.label(folder= getwd())
## End(Not run)
Select and merge data
Description
timssg8.select.merge selects and merges data from TIMSS G8.
Usage
timssg8.select.merge(folder = getwd(), countries, student = c(), school,
math.teacher, science.teacher)
Arguments
folder |
Directory path where the data are located. The data could be organized within folders but it should not be duplicated. |
countries |
The selected countries, supplied with the abbreviation (e.g., countries=c("AUT", "BGR") or codes (countries=c(40, 100)). If no countries are selected, all are selected. |
student |
The data labels for the selected student variables. |
school |
The data labels for the selected school variables. |
math.teacher |
The data labels for the selected math teacher variables. |
science.teacher |
The data labels for the selected science teacher variables. |
Value
timssg8.select.merge returns a data frame with the selected data from TIMSS G8.
See Also
timssg4.select.merge, pirls.select.merge, pisa.select.merge
Examples
## Not run:
timss8g <- timssg8.select.merge(folder=getwd(),
countries=c("AUS", "BHR", "ARM", "CHL"),
student =c("BSDGEDUP", "ITSEX", "BSDAGE", "BSBGSLM", "BSDGSLM"),
school =c("BCBGDAS", "BCDG03"))
## End(Not run)
Data labels
Description
timssg8.var.labels prints and saves variable labels and names of participating countries in a text file
Usage
timssg8.var.label(folder = getwd(), name = "Variable labels", output = getwd())
Arguments
folder |
Directory path where the TIMSS G8 data are located. The data could be organized within folders but it should not be duplicated. |
name |
Name of output file. |
output |
Folder where output file is located. |
Value
timssg8.var.label returns a list with variable labels for the student, home, school, and teacher data.
See Also
timssg4.var.label, pirls.var.label, pisa.var.label
Examples
## Not run:
timssg8.var.label(folder= getwd())
## End(Not run)