Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.

This paper presents the methodology for performing and interpreting second-order factor analysis. Procedures for extracting and rotating solutions are presented. Critical issues of interpretation, such as interpreting second-order factors are discussed. Two methods for accomplishing this are explained, including multiplying the first- and…

Data reduction techniques seek to combine variables that account for patterns of variation in observed dependent variables in such a way that a simpler model is available for analysis. Factor analysis is a data reduction technique that attempts to model or explain a set of variables in terms of their associations. To understand why this technique…

This paper briefly explains the possible two-mode techniques of factor analysis, and discusses, in more detail, one two-mode technique--the Q-technique. The Q-technique may be useful when the researcher is interested in obtaining information about "types" of individuals with regard to certain variables. A concrete heuristic example is used to…

This paper conceptually explains higher-order factor analysis and methods for interpretation. A review of first-order factor analysis is presented that provides the foundation for the summary of second-order factor analysis. Higher order factors are derived from the correlations between the lower-level factors. An example study is provided to make…