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Exploratory Factor Analysis With Small Samples and Missing Data.

Daniel McNeish1

  • 1a Department of Methodology and Statistics , Utrecht University , The Netherlands.

Journal of Personality Assessment
|December 9, 2016
PubMed
Summary
This summary is machine-generated.

Exploratory factor analysis (EFA) with small samples and missing data is common in psychology. Predictive mean matching best handles these issues, accurately extracting factors and estimating loadings without bias.

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Area of Science:

  • Psychometrics
  • Statistical Modeling

Background:

  • Exploratory Factor Analysis (EFA) is widely used but often applied with small sample sizes and incomplete data.
  • Existing research on handling missing data in EFA with small samples is limited and often focuses on irrelevant aspects.

Purpose of the Study:

  • To evaluate the performance of different missing data techniques for Exploratory Factor Analysis (EFA) under conditions of small sample sizes and missing data.
  • To identify the most effective methods for accurate factor extraction and loading estimation in challenging data scenarios.

Main Methods:

  • A simulation study was conducted to assess various missing data techniques.
  • The simulation focused on Exploratory Factor Analysis (EFA) models with both small sample sizes and missing data.

Main Results:

  • Deletion methods performed poorly, failing to extract the correct number of factors and introducing significant bias in factor loading estimates.
  • Predictive mean matching demonstrated superior performance, accurately identifying the number of factors and estimating loadings without bias.
  • Two-stage estimation was also found to be a strong performer, closely following predictive mean matching.

Conclusions:

  • Standard deletion methods are inadequate for EFA with small samples and missing data.
  • Predictive mean matching is recommended as the optimal technique for addressing missing data in EFA under these conditions.
  • Further research into robust missing data handling for EFA is warranted.