R Analyzer for Large-Scale Assessments
Compute percentages of respondents reaching or surpassing certain abil...
Compute binary logistic regression coefficients specified groups
Convert Large-Scale Assessments' Datasets to .RData Format
Convert Large-Scale Assessments' Datasets to .RData Format
Compute correlations between variables within specified groups
Compute crosstabulations and design corrected chi-square statistics
Produce data diagnostic tables
Compute linear regression coefficients specified groups
Merge study data from different countries and/or respondents
Compute percentages of respondents in groups and/or means (arithmetic ...
Compute percentiles of continuous variables within groups
Recode variables in large-scale assessments' data sets
Produce dictionary for large-scale assessments data variables
R Analyzer for Large-Scale Assessments (RALSA)
Start RALSA's Graphical User Interface (GUI)
Start RALSA's Graphical User Interface (GUI) in a failsafe mode
Prepare and analyze data from large-scale assessments and surveys with complex sampling and assessment design (see 'Rutkowski', 2010 <doi:10.3102/0013189X10363170>). Such studies are, for example, international assessments like 'TIMSS', 'PIRLS' and 'PISA'. A graphical interface is available for the non-technical user.The package includes functions to covert the original data from 'SPSS' into 'R' data sets keeping the user-defined missing values, merge data from different respondents and/or countries, generate variable dictionaries, modify data, produce descriptive statistics (percentages, means, percentiles, benchmarks) and multivariate statistics (correlations, linear regression, binary logistic regression). The number of supported studies and analysis types will increase in future. For a general presentation of the package, see 'Mirazchiyski', 2021a (<doi:10.1186/s40536-021-00114-4>). For detailed technical aspects of the package, see 'Mirazchiyski', 2021b (<doi:10.3390/psych3020018>).