nt structure analysis, latent class analysis, cluster analysis, and two variants of factor analysis (Pfaffenberger & Patterson, 1995).
The labor participation rate as a function of the selected demographic factors was assessed through the application of multiple regression analysis to the data collected. Multiple regression is a general statistical technique through which one can analyze the relationship between a dependent or criterion variable and a set of independent or predictor variables. Multiple regression may be viewed either as a descriptive tool by which the linear dependence of one variable on others is summarized and decomposed, or as an inferential tool by which the relationships in the population are evaluated from the examination of sample data (Pfaffenberger & Patterson, 1995).
Multiple regression is used as a descriptive tool in three types of situations: to develop a self-weighting estimating equation by which to predict values for a dependent variable; to control for confounding variables so as to better evaluate the contribution of other variables; and to test explicit causal th
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