ABSTRACT
This chapter discusses a restatement of the unitary factor variances, followed by the error term variances that are all significant. This finding indicates that for each of the indicators some nonnegligible portion of its variance is due to unaccounted by the model sources of variability, including measurement error. Like path analysis, factor analysis has a relatively long history. In general terms, factor analysis is a modeling approach for studying hypothetical constructs by using a variety of observable proxies or indicators of them that can be directly measured. The analysis is considered exploratory, also referred to as exploratory factor analysis (EFA), when the concern is with determining how many factors, or latent constructs, are needed to explain well the relationships among a given set of observed measures. Alternatively, the analysis is confirmatory, formally referred to as confirmatory factor analysis (CFA), when a preexisting structure of the relationships among the measures is being quantified and tested.
