Three different bootstrap methods for estimating confidence intervals (CIs) for coefficient alpha were investigated. In addition, the bootstrap methods were compared with the most promising coefficient alpha CI estimation methods reported in the literature. The CI methods were assessed through a Monte Carlo simulation utilizing conditions…

Relatively little research has been conducted with the noncompensatory class of multidimensional item response theory (MIRT) models. A Monte Carlo simulation study was conducted exploring the estimation of a two-parameter noncompensatory item response theory (IRT) model. The estimation method used was a Metropolis-Hastings within Gibbs algorithm…

This article presents an application of Monte Carlo methods for developing and assembling multistage adaptive tests (MSTs). A major advantage of the Monte Carlo assembly over other approaches (e.g., integer programming or enumerative heuristics) is that it provides a uniform sampling from all MSTs (or MST paths) available from a given item pool.…

Proposed a new asymptotic formula for estimating the sampling variance of a correlation coefficient corrected for unreliability and range restriction. A Monte Carlo simulation study of the new formula results in several positive conclusions about the new approach. (SLD)

Monte Carlo methodologies are frequently applied to study the sampling distribution of the estimated proficiency level in adaptive testing. These methods eliminate real situational constraints. However, these Monte Carlo methodologies are not currently supported by the available software programs, and when these programs are available, their…

A Monte Carlo simulation explored how to optimize power in the extreme groups strategy when sampling from nonnormal distributions. Results show that the optimum percent for the extreme group selection was approximately the same for all population shapes, except the extremely platykurtic (uniform) distribution. (SLD)

Three methods based on the nonparametric item response theory (IRT) of R. J. Mokken for the estimation of the reliability of single dichotomous test items are discussed. Analytical and Monte Carlo studies show that one method, designated "MS," is superior because of smaller bias and smaller sampling variance. (SLD)

A method is proposed for sequential evaluation of reliability of psychometric instruments. Sample size is unfixed; a test statistic is computed after each person is sampled and a decision is made in each stage of the sampling process. Results from a series of Monte-Carlo experiments establish the method's efficiency. (SLD)