Determining the number of factors in P-technique factor analysis. Issue 2 (3rd April 2017)

• Record Type: Journal Article
• Authors: Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael
• Is Part Of: Applied developmental science. Volume 21:Issue 2(2017)
• Page Start: 94
• Page End: 105
• Publication Date: 2017-04-03
• Subjects: Child development -- Periodicals; Developmental psychology -- Periodicals; 305.231
• DOI: 10.1080/10888691.2016.1173549
• Languages: English
• ISSNs: 1088-8691

Abstract

ABSTRACT: Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A novel feature of P-technique data is that observations are usually sequentially dependent in some way. The current study evaluates 10 criteria for determining the number of factors for data simulated to resemble intensive repeated-measures data for which P-technique is usually applied. The number of factors, loading size, observed-to-latent ratio, serial-dependency, and sample size were simulation design factors with conditions simulated to resemble P-technique data. The methods are compiled from various statistical techniques and have been demonstrated in previous R-technique simulations. Finally, a real data example demonstrates applying the acceleration factor method to several time series data sets.