American Institutes for Research and Jon Cohen. (n.d.). AM.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B (Methodological), 57(1), 289–300.
Binder, D. A. (1983). On the variances of asymptotically normal estimators from complex surveys. International Statistical Review/Revue Internationale de Statistique, 51(3), 279–292.
Caro, D. H., & Biecek, P. (2017). Intsvy: An r package for analyzing international large-scale assessment data. Journal of Statistical Software, 81(7), 1–44.
Cohen, J. D., & Jiang, T. (1999). Comparison of partially measured latent traits across nominal subgroups. Journal of the American Statistical Association, 94(448), 1035–1044.
Educational Progress, N. A. of. (2018). NAEP technical documentation on the web. National Center for Education Statistics.
Johnson, E. G., & Rust, K. F. (1992). Population inferences and variance estimation for NAEP data. Journal of Statistical Software, 17(2), 175–190.
Judkins, D. R. (1990). Fay’s method for variance estimation. Journal of Official Statistics, 6(3), 223–239.
Korn, E. L., & Graubard, B. I. (1990). Simultaneous testing of regression coefficients with complex survey data: Use of bonferroni t statistics. The American Statistician, 44(4), 270–276.
LaRoche, S., Joncas, M., & Foy, P. (2016). Sample design in TIMSS 2015 (&. M. H. M. O. Martin I. V. S. Mullis, Ed.; pp. 3.1–3.37).
Lumley, T. (2004). Analysis of complex survey samples. Journal of Statistical Software, 9(8), 1–19.
Manuel, R., & Peterbauer, J. (2014). A package for complex surveys including plausible values.
R package version 0.1-1
Mislevy, R. J., Beaton, A., Kaplan, B. A., & Sheehan, K. (1992). Estimating population characteristics from sparse matrix samples of item responses. Journal of Educational Measurement, 29(2), 133–161.
Oberski, D. (2017). An r package for complex survey analysis of structural equation models. Journal of Statistical Software, 57(1), 1–27.
OECD. (2018). PISA 2018 technical report. Organization for Economic Co-operation; Development (OECD).
R Core Team. (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing.
Robitzsch, A., & Oberwimmer, K. (2019). BIFIEsurvey: Tools for survey statistics in educational assessment. Federal Institute for Educational Research, Innovation; Development of the Austrian School System.
R package version 3.3-12
Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. Wiley.
Rust, K. F., & Rao, J. N. K. (1996). Replication methods for analyzing complex survey data. Statistical Methods in Medical Research: Special Issue on the Analysis of Complex Surveys, 5, 283–310.
Rutkowski, L., Gonzalez, E., Joncas, M., & Davier, M. von. (2010). International large-scale assessment data: Issues in secondary analysis and reporting. Educational Researcher, 39(2), 142–151.
Satterthwaite, F. E. (1946). An approximate distribution of estimates of variance components. Biometrics Bulletin, 2(6), 110–114.
Weisberg, S. (1985). Applied linear regression. Wiley.
Welch, B. L. (1947). The generalization of ‘student’s’ problem when several different population variances are involved. Biometrika, 34(1/2), 28–35.
Wolter, K. (2007). Introduction to variance estimation (2nd ed.). Springer Science & Business Media.