Document Type
Article
Publication Date
2025
Keywords
measurement invariance, item parceling, distributed parceling, isolated parceling, fit measures
Abstract
Item parceling is common in structural equation modeling used in psychology, especially when the research interest is in the structural relationship between latent factors, but research on its performance in measurement invariance testing is scarce. This study examined the sensitivity of fit measures (LRT, RMSEA, CFI, AIC, BIC, and SaBIC) to measurement noninvariance with different numbers of items per parcel and parceling strategies using a simulation study. The design factors included the location of measurement noninvariance, the magnitude of measurement noninvariance, the proportion of items with measurement noninvariance, sample size, number of items per parcel, and parceling strategies. Results suggested that compared to no parceling, isolated parceling tended to increase the sensitivity of fit measures, especially when fewer parcels with more items per parcel were used; distributed parceling showed lower sensitivity, particularly when noninvariant items were evenly distributed and fewer parcels were used. The findings provide insights into the use parceling in examining the relationship between constructs. The paper concludes with practical implications and future research directions.
Citation
Cao, Chunhua, Liang, Xinya (2025). Exploring the Effect of Item Parceling Strategies and Number of Items per Parcel on Measurement Invariance Testing in Confirmatory Factor Analysis. The Quantitative Methods for Psychology, 21(2), 95-107. doi: 10.20982/tqmp.21.2.p095
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Comments
Web of Science