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Statistical methodology: VIII. Using confirmatory factor analysis (CFA) in emergency medicine research
F B Bryant1, P R Yarnold, E A Michelson
1Department of Psychology, Loyola University Chicago, IL 60626, USA. fbryant@luc.edu
Summary
Confirmatory factor analysis (CFA) helps determine the number of underlying factors in survey data. Researchers can use CFA to evaluate and refine models for better instrument precision and data representation.
Area of Science:
- Psychometrics
- Statistical modeling
- Health services research
Background:
- Determining the number of underlying factors in survey data is crucial for accurate analysis.
- Researchers face choices in analyzing survey responses: individually, as a global score, or by factor grouping.
Purpose of the Study:
- To describe the principles and applications of Confirmatory Factor Analysis (CFA).
- To demonstrate how CFA can be used to evaluate, compare, and refine factor models in research.
Main Methods:
- The study utilizes Confirmatory Factor Analysis (CFA) to analyze survey data.
- A dataset of 1,614 emergency medical patient satisfaction responses was analyzed.
Main Results:
- CFA allows for the comparison of competing factor models to identify the best fit.
- Models can be modified to improve goodness-of-fit, and hypotheses about factor relationships can be tested.
Conclusions:
- CFA is a valuable tool for assessing the explanatory power of factor models and refining survey instruments.
- The method aids in developing streamlined instruments with improved conceptual and statistical precision.
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