Reweighting a distribution to minimize a distance to a target distribution is a powerful and flexible strategy for estimating a wide range of causal effects, but can be challenging in practice because optimal weights typically depend on knowledge of the underlying data generating process. In this paper, we focus on design-based weights, which do…

In analyzing exploratory repeated measures data with more than two measures, two competing tests must be administered simultaneously if one is to make an efficient and effective decision regarding the tenability of the null hypothesis of no differences among measurement means. Obviously, such a procedure is not without a cost vis-a-vis Type I…

This Monte Carlo investigation provides some possible solutions to problems related to choosing multiple-comparison methods that maximize true rejections and minimize false ones. It has been argued that the traditional Bonferroni approach to multiple comparisons, which satisfies the statistician's family-wise Type I error concerns, could be…

The use of stepwise regression has been criticized for both interpretive misunderstandings and statistical aberrations. A major statistical problem with stepwise regression and other procedures that involve multiple significance tests is the inflation of the Type I error rate. General approaches to control the family-wise error rate such as the…

Advantages and disadvantages of standard Rasch analysis computer programs are discussed. The unconditional maximum likelihood algorithm allows all observations to participate equally in determining the measures and calibrations to be obtained quickly from a data set. On the advantage side, standard Rasch programs can be used immediately, are…