How to factor-analyze your data right: do’s, don’ts, and how-to’s.

Abstract

Cómo analizar factorialmente tus datos: qué significa, qué no significa, y cómo hacerlo. Masaki MatsunagaRikkyo University ABSTRACTThe current article provides a guideline for conducting factor analysis, a technique used to estimate the populationlevel factor structure underlying the given sample data. First, the distinction between exploratory and confirmatory factor analyses (EFA and CFA) is briefly discussed; along with this discussion, the notion of principal component analysis and why it does not provide a valid substitute of factor analysis is noted. Second, a step-by-step walk-through of conducting factor analysis is illustrated; through these walk-through instructions, various decisions that need to be made in factor analysis are discussed and recommendations provided. Specifically, suggestions for how to carry out preliminary procedures, EFA, and CFA are provided with SPSS and LISREL syntax examples. Finally, some critical issues concerning the appropriate (and not-so-appropriate) use of factor analysis are discussed along with the discussion of recommended practices. Key words: Confirmatory and Exploratory Factor Analysis LISREL -Parallel Analysis -Principal Component Analysis -SPSS RESUMENEl presente artículo provee una guía para conducir análisis factorial, una técnica usada para estimar la estructura de las variables a nivel de la población que subyacen a los datos de la muestra. Primero, se hace una distinción entre análisis factorial exploratorio (AFE) y análisis factorial confirmatorio (AFC) junto con una discusión de la noción de análisis de componentes principales y por qué este no reemplaza el análisis de factores. Luego, se presenta una guía acerca de cómo hacer análisis factorial y que incluye decisiones que deben tomarse durante el análisis factorial. En especial, se presentan ejemplos en SPSS y LISREL acerca de cómo llevar a cabo procedimientos preliminares, AFE y AFC. Finalmente, se discuten asuntos clave en relación con el uso apropiado del análisis de factores y practicas recomendables.Palabras clave: Análisis factorial confirmatorio y exploratorio, LISREL, análisis paralelo, análisis de componentes principales, SPSS.

The Parent Trauma Response Questionnaire (PTRQ): development and preliminary validation

“…The number of factors to retain was based on several criteria: (1) a visual examination of the scree plot; (2) parallel analysis using the Monte-Carlo program; and (3) considerations regarding the meaning and interpretability of the factor model. Items that loaded more than .5 on a primary factor and less than .3 on remaining factors were retained (Matsunaga, 2011). Items that did not load more than .5 on a primary factor could be retained so long as these items had loadings of less than .3 on secondary factors and their inclusion improved the internal consistency of the subscales.…”

Development and initial validation of a measure of metacognitive beliefs in health anxiety: The MCQ-HA

“…Eigenvalues above 1 was selected as this is considered appropriate when running a primary analysis of data screening (Field, 2013;Matsunaga, 2010). As there was a potential for the items in this measure to be correlated, as has been shown in other metacognitive measures, i.e.…”

The Adolescent Self-Regulatory Inventory (ASRI) Adaptation to Portuguese Context

“…Fourteen items theoretically related to short-term self-regulation and 13 to long-term dimension were mixed with the existing items of the ASRI and administered again with the SRS (Schwarzer, 1999) to analyse concurrent validity. Confirmatory Factor Analysis was used to ensure that the psychometric properties of the measure are theoretically and empirically sound (Henson & Roberts, 2006;Matsunaga, 2010) with a sample between 200 and 500 adolescents, according to literature (Pilati & Laros, 2007).…”

“…To this instrumental study, the requirements for the adaptation of psychological measures were followed (Borsa, Damásio, & Bandeira, 2012;Carretero-Dias & Pérez, 2007), considering two studies with independent samples to evaluate the factor structure, with exploratory and confirmatory factor analysis (Henson & Roberts, 2006). Despite both might be used to the validity evaluation, the first one is specially used for theorybuilding, while the second one is used primarily for theorytesting (Henson & Roberts, 2006;Matsunaga, 2010). That way, we start exploring the latent structure of the measure in Portuguese population to deepen our analysis and confirm the theoretical model in the second study.…”