MSA: The Forgotten Index for Identifying Inappropriate Items Before Computing Exploratory Item Factor Analysis

Identificador:  imarina:9243291

Handle: https://hdl.handle.net/20.500.11797/imarina9243291

Autors:  Lorenzo-Seva, Urbano; Ferrando, Pere J

Resum:
Kaiser's single-variable measure of sampling adequacy (MSA) is a very useful index for debugging inappropriate items before a factor analysis (FA) solution is fittedto an item-pool dataset for item selection purposes. For reasons discussed in the article, however, MSA is hardly used nowadays in this context. In our view, this is unfortunate. In the present proposal, we firstdiscuss the foundation and rationale of MSA from a 'modern' FA view, as well as its usefulness in the item selection process. Second, we embed the index within a robust approach and propose improvements in the preliminary item selection process. Third, we implement the proposal in different statistical programs. Finally, we illustrate its use and advantages with an empirical example in personality measurement.