The released EdSurvey Version 2.0 is designed for the analysis of national and international education data from the National Center for Education Statistics (NCES), including the following data sources:

• National Assessment of Educational Progress (NAEP)
• Trends in International Mathematics and Science Study (TIMSS) and TIMSS Advanced
• Progress in International Reading Literacy Study (PIRLS)
• International Computer and Information Literacy Study (ICILS)
• International Civic and Citizenship Education Study (ICCS)
• Civic Education Study (CivEd)
• Programme for International Student Assessment (PISA)
• Programme for the International Assessment of Adult Competencies (PIAAC)
• Teaching and Learning International Survey (TALIS)

EdSurvey gives users the ability to process and analyze these data efficiently, taking into account their complex sample survey design and the use of plausible values.

EdSurvey: Installation and Use >>

EdSurvey is an R statistical package developed by AIR and commissioned by the National Center for Education Statistics (NCES). EdSurvey is tailored to the processing and analysis of NCES large-scale education data with appropriate procedures.

The key functions of EdSurvey Version 2.0 include

• data processing, including downloading public available data and reading data in R;
• data manipulation, including subsetting and merging data and renaming and recoding variables;
• cross-tabulation, including unweighted and weighted totals, conditional means, and the percentage of respondents in a category (conditional on an ancillary categorical variable or on the interactions of an arbitrary number of categorical variables), estimation of scale score means based on plausible values;
• percentile that calculates the percentiles of a numeric variable or plausible values;
• analysis of achievement levels and benchmarks for NAEP and international assessment data;
• correlations, including Pearson, Spearman, polyserial, polychoric, and correlation between plausible values, with or without weights applied;
• linear regression with or without plausible values as the dependent variable;
• logistic regression that allows either a discrete variable or dichotomized plausible values as the dependent variable; and
• gap analysis that compares the average, percentile, achievement level, or percentage of survey responses between two groups that potentially share members.

As the development of EdSurvey progresses, several additional functions, such as multilevel mixed model and multivariate regression, will be added.

The following are technical papers related to this project:

• Analyses Using Achievement Levels Based on Plausible Values
• Calculating Adjusted p-Values From EdSurvey Results (PDF)
• Exploratory Data Analysis on NCES Data (PDF)
• Methods and Overview of Using EdSurvey for Multivariate Regression (PDF)
• Methods and Overview of Using EdSurvey for Running Wald Tests (PDF)
• Methods Used for Estimating Mixed-Effects Models in EdSurvey (PDF)
• Methods Used for Estimating Percentiles in EdSurvey (PDF)
• Methods Used for Gap Analysis in EdSurvey (PDF)
• Producing LaTeX Tables From edsurveyTable Results With edsurveyTable2pdf (PDF)
• Statistical Methods Used in EdSurvey (PDF)
• Using EdSurvey for Trend Analysis (PDF)
• Using EdSurvey to Analyze NAEP Data With and Without Accommodations (PDF)
• Using EdSurvey to Analyze NCES Data: An Illustration of Analyzing NAEP Primer (PDF)
• Using EdSurvey to Analyze TIMSS Data (PDF)
• Using the getData Function in EdSurvey (PDF)
• Weighted and Unweighted Correlation Methods for Large-Scale Educational Assessment: wCorr Formulas