This is a practical guide for applying the Impact Threshold for a Confounding Variable and the Robustness of Inference to Replacement using the konfound packages in Stata and R as well as the R-shiny app. It includes motivation worked examples, and tutorials.

Among current state-of-art estimation methods for multilevel IRT models, the two-stage divide-and-conquer strategy has practical advantages, such as clearer definition of factors, convenience for secondary data analysis, convenience for model calibration and fit evaluation, and avoidance of improper solutions. However, various studies have shown…

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the…