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An Analysis Of Factor Extraction Strategies: A Comparison Of The Relative Strengths Of Principal Axis, Ordinary Least Squares, And Maximum Likelihood In Research Contexts That Include Both Categorical And Continuous Variables, Kevin Barry Coughlin
USF Tampa Graduate Theses and Dissertations
This study is intended to provide researchers with empirically derived guidelines for conducting factor analytic studies in research contexts that include dichotomous and continuous levels of measurement. This study is based on the hypotheses that ordinary least squares (OLS) factor analysis will yield more accurate parameter estimates than maximum likelihood (ML) and principal axis factor anlaysis (PAF); the level of improvement in estimates will be related to the proportion of observed variables that are dichotomized and the strength of communalities within the data sets.
To achieve this study's objective, maximum likelihood, ordinary least squares, and principal axis factor extraction models …