EdSurvey - Analysis of NCES Education Survey and Assessment Data

Read in and analyze functions for education survey and assessment data from the National Center for Education Statistics (NCES) <https://nces.ed.gov/>, including National Assessment of Educational Progress (NAEP) data <https://nces.ed.gov/nationsreportcard/> and data from the International Assessment Database: Organisation for Economic Co-operation and Development (OECD) <https://www.oecd.org/>, including Programme for International Student Assessment (PISA), Teaching and Learning International Survey (TALIS), Programme for the International Assessment of Adult Competencies (PIAAC), and International Association for the Evaluation of Educational Achievement (IEA) <https://www.iea.nl/>, including Trends in International Mathematics and Science Study (TIMSS), TIMSS Advanced, Progress in International Reading Literacy Study (PIRLS), International Civic and Citizenship Study (ICCS), International Computer and Information Literacy Study (ICILS), and Civic Education Study (CivEd).

Last updated 3 months ago

7.84 score 10 stars 1 dependents 132 scripts 683 downloads

wCorr - Weighted Correlations

Calculates Pearson, Spearman, polychoric, and polyserial correlation coefficients, in weighted or unweighted form. The package implements tetrachoric correlation as a special case of the polychoric and biserial correlation as a specific case of the polyserial.

Last updated 1 years ago

openblascppopenmp

6.39 score 7 dependents 118 scripts 927 downloads

WeMix - Weighted Mixed-Effects Models Using Multilevel Pseudo Maximum Likelihood Estimation

Run mixed-effects models that include weights at every level. The WeMix package fits a weighted mixed model, also known as a multilevel, mixed, or hierarchical linear model (HLM). The weights could be inverse selection probabilities, such as those developed for an education survey where schools are sampled probabilistically, and then students inside of those schools are sampled probabilistically. Although mixed-effects models are already available in R, WeMix is unique in implementing methods for mixed models using weights at multiple levels. Both linear and logit models are supported. Models may have up to three levels. Random effects are estimated using the PIRLS algorithm from 'lme4pureR' (Walker and Bates (2013) <https://github.com/lme4/lme4pureR>).

Last updated 3 months ago

6.28 score 10 stars 2 dependents 32 scripts 688 downloads

Dire - Linear Regressions with a Latent Outcome Variable

Fit latent variable linear models, estimating score distributions for groups of people, following Cohen and Jiang (1999) <doi:10.2307/2669917>. In this model, a latent distribution is conditional on students item response, item characteristics, and conditioning variables the user includes. This latent trait is then integrated out. This software is intended to fit the same models as the existing software 'AM' <https://am.air.org/>. As of version 2, also allows the user to draw plausible values.

Last updated 1 years ago

cpp

4.48 score 1 stars 2 dependents 4 scripts 399 downloads