TY - JOUR
T1 - The Impact of Partial Measurement Invariance on Between-group Comparisons of Second-Order Factor Means
AU - Liu, Yixing
AU - Thompson, Marilyn S.
N1 - Funding Information:
We appreciate suggestions and feedback on this research received from Samuel Green and Roy Levy from Arizona State University.
Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.
PY - 2022
Y1 - 2022
N2 - A simulation study was conducted to explore the influence of partial measurement invariance on the second-order factor mean difference estimation. The types, positions, numbers, and directions of between-group differences for noninvariant parameters were manipulated, along with sample size and effect size of the latent mean difference. When the model was misspecified by constraining noninvariant loadings or intercepts to be equal, the latent mean difference was overestimated if the direction of the difference in noninvariant parameters was consistent with the direction of the latent mean difference, and vice versa. The numbers, types, and positions of noninvariant parameters also had an influence on the estimation bias. Power to detect the latent mean difference was influenced by the corresponding estimation bias and estimated variance, in addition to sample size and effect size.
AB - A simulation study was conducted to explore the influence of partial measurement invariance on the second-order factor mean difference estimation. The types, positions, numbers, and directions of between-group differences for noninvariant parameters were manipulated, along with sample size and effect size of the latent mean difference. When the model was misspecified by constraining noninvariant loadings or intercepts to be equal, the latent mean difference was overestimated if the direction of the difference in noninvariant parameters was consistent with the direction of the latent mean difference, and vice versa. The numbers, types, and positions of noninvariant parameters also had an influence on the estimation bias. Power to detect the latent mean difference was influenced by the corresponding estimation bias and estimated variance, in addition to sample size and effect size.
KW - Second-order factor models
KW - partial measurement invariance
KW - second-order factor mean difference
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U2 - 10.1080/10705511.2021.1936535
DO - 10.1080/10705511.2021.1936535
M3 - Article
AN - SCOPUS:85111694605
VL - 29
SP - 86
EP - 100
JO - Structural Equation Modeling
JF - Structural Equation Modeling
SN - 1070-5511
IS - 1
ER -