Journal
EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT
Volume 79, Issue 2, Pages 310-334Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/0013164418783530
Keywords
model size effect; structural equation modeling (SEM); fit indices
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Funding
- National Research Foundation of Korea (NRF) - Korea government(MSIP) [2017R1C1B2012424]
- National Science Foundation [SES-1659936]
- National Research Foundation of Korea [2017R1C1B2012424] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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This study investigated the effect the number of observed variables (p) has on three structural equation modeling indices: the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). The behaviors of the population fit indices and their sample estimates were compared under various conditions created by manipulating the number of observed variables, the types of model misspecification, the sample size, and the magnitude of factor loadings. The results showed that the effect of p on the population CFI and TLI depended on the type of specification error, whereas a higher p was associated with lower values of the population RMSEA regardless of the type of model misspecification. In finite samples, all three fit indices tended to yield estimates that suggested a worse fit than their population counterparts, which was more pronounced with a smaller sample size, higher p, and lower factor loading.
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