A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

Stepwise regression is not an adequate technique to provide the best set of variables with which to predict the dependent variable. By using the stepwise regression method, one who attempts to select the best set of predictors of a given dependent variable will face more problems than he or she attempted to resolve. This is illustrated with an…

A Rasch measurement model can be constructed to meet the requirements of rank ordered data. If multiple rankings of the same objects are available, then the parameters of the objects can be estimated, along with their standard errors and also with statistics summarizing the fit of the data to the measurement model. This paper summarizes the…

Published studies of the sampling distribution of chi-square with and without Yates' correction for continuity have been interpreted as discrediting the correction. Yates' correction actually produces a biased chi-square value which in turn yields a better estimate of the exact probability of the discrete event concerned when used in conjunction…

Often, all of the variables in a model are latent, random, or subject to measurement error, or there is not an obvious dependent variable. When any of these conditions exist, an appropriate method for estimating the linear relationships among the variables is Least Principal Components Analysis. Least Principal Components are robust, consistent,…

This Monte Carlo study examined the validity of the chi-square test for model evaluation in different instances of misspecification and sample size. The usefulness of the chi-square difference statistic to compare competing structures and improvement in fit is also addressed. (Author/BS)

Over the last 15 years or so, research into measurement error has begun to consider not just whether the test items fit, but whether the people who answer the items fit. Attempts to systematically identify people who do not fit the typical pattern have led to several "person-fit statistics." This digest describes the need for such…

One of the most frequently used research methods in education and psychology involves repeated observations on the same individuals. When sample sizes are relatively small and a multivariate analysis lacks power, there are currently two analytical options in testing time effects. One is to assume a time series structure to these observations, and…

The logic of using a gain score approach versus longitudinal causal models is studied in this secondary analysis of a complex data base. The gain score model used by the Federal Reserve Bank and the School District of Philadelphia in their "What Works in Reading?" study is successively refined using the LISREL structural equation…

The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…