Data are everywhere. Data collected from samples are often reported in the form of polls, medical studies, and advertisement information and an understanding of sampling distributions and statistical inference is important for evaluating data-based claims (Bargagliotti et al., 2020). Despite the importance of understanding statistical inference…

Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…

Model-based methods for estimating the population mean in stratified clustered sampling are described. The importance of adjusting the weights is assessed by an approach considering the sampling variation of the adjusted weights and its (variance) components. The resulting estimators are more efficient than the jackknife estimators for a variety…