When estimating causal effects, unmeasured confounding and model misspecification are both potential sources of bias. We propose a method to simultaneously address both issues in the form of a semi-parametric sensitivity analysis. In particular, our approach incorporates Bayesian Additive Regression Trees into a two-parameter sensitivity analysis…

The difference between item bias and item impact and the way they relate to item validity are discussed from a multidimensional item response theory perspective. The Mantel-Haenszel procedure and the Simultaneous Item Bias strategy are used in a Monte Carlo study to illustrate detection of item bias. (SLD)