Abstract
In recent years, confirmatory factor analytic (CFA) techniques have become the most common method of testing for measurement equivalence/invariance (ME/I). However, no study has simulated data with known differences to determine how well these CFA techniques perform. This study utilizes data with a variety of known simulated differences in factor loadings to determine how well traditional tests of ME/I can detect these specific simulated differences. Results show that traditional CFA tests of ME/I perform well under ideal situations but that large sample sizes, a sufficient number of manifest indicators, and at least moderate communalities are crucial for assurance that ME/I conditions exist.
Keywords
Equivalence (formal languages)Monte Carlo methodMeasurement invarianceConfirmatory factor analysisStatisticsFactor analysisMathematicsSample size determinationEconometricsStructural equation modelingDiscrete mathematics
Affiliated Institutions
Related Publications
Mean and Covariance Structures (MACS) Analyses of Cross-Cultural Data: Practical and Theoretical Issues
Practical and theoretical issues are discussed for testing (a) the comparability, or measurement equivalence, of psychological constructs and (b) detecting possible sociocultura...
How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power
Abstract A common question asked by researchers is, "What sample size do I need for my study?" Over the years, several rules of thumb have been proposed. In reality there is no ...
Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance
Two Monte Carlo studies were conducted to examine the sensitivity of goodness of fit indexes to lack of measurement invariance at 3 commonly tested levels: factor loadings, inte...
Teacher's Corner: Testing Measurement Invariance of Second-Order Factor Models
We illustrate testing measurement invariance in a second-order factor model using a quality of life dataset (n = 924). Measurement invariance was tested across 2 groups at a set...
Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance
Abstract Measurement invariance is usually tested using Multigroup Confirmatory Factor Analysis, which examines the change in the goodness-of-fit index (GFI) when cross-group co...
Publication Info
- Year
- 2004
- Type
- article
- Volume
- 11
- Issue
- 1
- Pages
- 60-72
- Citations
- 185
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
185
OpenAlex
Cite This
Adam W. Meade,
Gary J. Lautenschlager
(2004).
A Monte-Carlo Study of Confirmatory Factor Analytic Tests of Measurement Equivalence/Invariance.
Structural Equation Modeling A Multidisciplinary Journal
, 11
(1)
, 60-72.
https://doi.org/10.1207/s15328007sem1101_5
Identifiers
- DOI
- 10.1207/s15328007sem1101_5