This dissertation develops and applies sophisticated Item Response Theory (IRT) methods to address fundamental measurement challenges in cognitive testing, focusing on the Armed Services Vocational Aptitude Battery (ASVAB) data from the National Longitudinal Survey of Youth (NLSY). The first chapter implements a confirmatory multidimensional IRT…

A method for selecting between K-dimensional linear factor models and (K + 1)-class latent profile models is proposed. In particular, it is shown that the conditional covariances of observed variables are constant under factor models but nonlinear functions of the conditioning variable under latent profile models. The performance of a convenient…

The effectiveness of 19 methods of smoothing was investigated as those methods apply to the equipercentile method of test equating. Seven methods involved smoothing the score distribution before the tests were equated (presmoothing). Seven involved smoothing the resultant points after the equating (postsmoothing). Five methods involved combining…

Using simulated item response data, the performance of several "robust" and conventional schemes for ability estimation was evaluated in conjunction with logistic item response theory models (one, two, and three parameter models). The simulated item response data were generated using a model that is more complex than are the usual…

How accurately ability is estimated when the test model does not fit the data is considered. To address this question, this study investigated the accuracy of the maximum likelihood estimator of ability for the one-, two- and three-parameter logistic (PL) models. The models were fitted into generated item characteristic curves derived from the…