Measurement error affects the quality of population orderings of an index and, hence, increases the misclassification of the poor and the non-poor groups and affects statistical inferences from binary regression models. Hence, the conclusions about the extent, profile, and distribution of poverty are likely to be misleading. However, the size and…

Survival analysis is an important analytic method in the social and medical sciences. Also known under the name time-to-event analysis, this method provides parameter estimation and model fitting commonly conducted via maximum-likelihood. Bayesian survival analysis offers multiple advantages over the frequentist approach for measurement…

Events such as curriculum changes or practice effects can lead to item parameter drift (IPD) in computer adaptive testing (CAT). The current investigation introduced a point- and weight-adjusted D[superscript 2] method for IPD detection for use in a CAT environment when items are suspected of drifting across test administrations. Type I error and…

Bayesian item response theory (IRT) modeling stages include (a) specifying the IRT likelihood model, (b) specifying the parameter prior distributions, (c) obtaining the posterior distribution, and (d) making appropriate inferences. The latter stage, and the focus of this research, includes model criticism. Choice of priors with the posterior…

The commentaries include a wealth of insightful and interesting observations and suggestions, and I appreciate each author taking the time to comment on my efforts. In responding to their suggestions, I am inclined to develop a few general points raised in the commentaries a bit further.

The theories of validity developed over the past 60 years are quite sophisticated, but the methodology of validity is not generally very effective. The validity evidence for major testing programs is typically much weaker than the evidence for more technical characteristics such as reliability. In addition, most validation efforts have a strong…