Connect to PIRLS Data

Opens a connection to a PIRLS data file and returns an edsurvey.data.frame with information about the file and data.

Usage

readPIRLS(path, countries, forceReread = FALSE, verbose = TRUE)

Arguments

path: a character value to the full directory path to the PIRLS extracted SPSS (.sav) set of data
countries: a character vector of the country/countries to include using the three-digit ISO country code. A list of country codes can be found on Wikipedia at https://en.wikipedia.org/wiki/ISO_3166-1#Current_codes or other online sources. Consult the PIRLS User Guide to help determine what countries are included within a specific testing year of PIRLS. To select all countries, use a wildcard value of *.
forceReread: a logical value to force rereading of all processed data. The default value of FALSE will speed up the readPIRLS function by using existing read-in data already processed.
verbose: a logical value to either print or suppress status message output. The default value is TRUE.

Value

an edsurvey.data.frame for a single specified country or an edsurvey.data.frame.list if multiple countries specified

Details

Reads in the unzipped files downloaded from the PIRLS international database(s) using the IEA Study Data Repository. Data files require the SPSS data file (.sav) format using the default filenames.

A PIRLS edsurvey.data.frame includes three distinct data levels:

student
school
teacher

When the getData function is called using a PIRLS edsurvey.data.frame, the requested data variables are inspected, and it handles any necessary data merges automatically. The school data always will be returned merged to the student data, even if only school variables are requested. If teacher variables are requested by the getData call, it will cause teacher data to be merged. Many students can be linked to many teachers, which varies widely between countries.

Please note that calling the dim function for a PIRLS edsurvey.data.frame will result in the row count as if the teacher dataset was merged. This row count will be considered the full data N of the edsurvey.data.frame, even if no teacher data were included in an analysis. The column count returned by dim will be the count of unique column variables across all three data levels.

Author

Tom Fink

Examples

if (FALSE) { # \dontrun{
nor <- readPIRLS("~/PIRLS/2011", countries = c("nor"))
gg <- getData(data=nor, varnames=c("itsex", "totwgt", "rrea"))
head(gg)
edsurveyTable(formula=rrea ~ itsex, nor)
} # }