In the social sciences, estimating causal effects is particularly difficult. Gold standards are set by randomized experiments in many cases expensive, unenforceable for ethical and practical reasons. Recent research has drawn attention to techniques that under some conditions, could estimate causal effects on non-experimental observable data. One…

Model-based multiple imputation has become an indispensable method in the educational and behavioral sciences. Mean and covariance structure models are often fitted to multiply imputed data sets. However, the presence of multiple random imputations complicates model fit testing, which is an important aspect of mean and covariance structure…