Improving Your Exploratory Factor Analysis for Ordinal Data: A Demonstration Using FACTOR
James Baglin
Abstract
Exploratory factor analysis (EFA) methods are used extensively in the field of assessment and evaluation. Due to EFA’s widespread use, common methods and practices have come under close scrutiny. A substantial body of literature has been compiled highlighting problems with many of the methods and practices used in EFA, and, in response, many guidelines have been proposed with the aim to improve application. Unfortunately, implementing recommended EFA practices has been restricted by the range of options available in commercial statistical packages and, perhaps, due to an absence of clear, practical ‘how-to’ demonstrations. Consequently, this article describes the application of methods recommended to get the most out of your EFA. The article focuses on dealing with the common situation of analysing ordinal data as derived from Likert-type scales. These methods are demonstrated using the free, stand-alone, easy-to-use and powerful EFA package FACTOR (http://psico.fcep.urv.es/utilitats/factor/, Lorenzo-Seva & Ferrando, 2006). The demonstration applies the recommended techniques using an accompanying dataset, based on the Big 5 personality test. The outcomes obtained by the EFA using the recommended procedures through FACTOR are compared to the default techniques currently available in SPSS. Accessed 23,681 times on https://pareonline.net from June 14, 2014 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.