Publication | Closed Access
Factor Retention Decisions in Exploratory Factor Analysis: a Tutorial on Parallel Analysis
3K
Citations
34
References
2004
Year
Customer SatisfactionEngineeringFactor ModelsMinnesota Satisfaction QuestionnairePsychometricsFactor Retention DecisionsOrganizational BehaviorHuman FactorParallel AnalysisLatent ModelingData ScienceData MiningManagementFactor AnalysisStatisticsLatent Variable ModelMarketingExploratory Factor AnalysisMatrix FactorizationConfirmatory Research
The decision of how many factors to retain is a critical component of exploratory factor analysis. Evidence is presented that parallel analysis is one of the most accurate factor retention methods while also being one of the most underutilized in management and organizational research. Therefore, a step-by-step guide to performing parallel analysis is described, and an example is provided using data from the Minnesota Satisfaction Questionnaire. Recommendations for making factor retention decisions are discussed.
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