Categorical data become increasingly ubiquitous in the modern big data era. In this dissertation, we propose novel statistical learning and inference methods for large-scale categorical data, focusing on latent variable models and their applications to psychometrics. In psychometric assessments, the subjects' underlying aptitude often cannot be…

Special cases of the factor analysis model are developed for four selection situations. Methods are suggested whereby parameters in each case can be estimated using a maximum likelihood procedure recently developed by Joreskog. (Author)

This study involved an investigation of the use of Pearson r, tetrachoric r, phi, phi/phi maximum, and Kendall Tau-B coefficients as measures of association for the incomplete principal components analysis of simulated Likert scale attitudinal data, based on a known factor pattern and possessing different types of severe departures from normality.…

This paper discusses the Lens Model' approach to the analysis of subject performance in multiple-cue judgment tasks embedded in probabilistic environments. (Author/RK)

The school district fiscal capacity data (1962 and 1967) of the National Finance Project were analyzed for psychometric adequacy and robustness of component composition. The procedures involved: (1) the computation of the Kaiser, Meyer, Olkin Measure of Sampling Adequacy, (2) inspection of the off-diagonal elements of the antiimage covariance…

A reliability study of the Brigance Comprehensive Inventory of Basic Skills (CIBS) is presented. All test-data collectors were provided onsite training in the administration and scoring of the CIBS. The sample included 85 black and 319 white students from grades two through eight, from parochial and private schools, in a southeastern metropolitan…