A systematic review of and reflection on the applications of factor mixture modeling.
Factor mixture modeling (FMM) incorporates both continuous latent variables and
categorical latent variables in a single analytic model clustering items and observations …
categorical latent variables in a single analytic model clustering items and observations …
Robustness of latent profile analysis to measurement noninvariance between profiles
Latent profile analysis (LPA) identifies heterogeneous subgroups based on continuous
indicators that represent different dimensions. It is a common practice to measure each …
indicators that represent different dimensions. It is a common practice to measure each …
Multilevel Factor Mixture Modeling: A Tutorial for Multilevel Constructs
C Cao, Y Wang, E Kim - Structural Equation Modeling: A …, 2024 - Taylor & Francis
Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis
(CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population …
(CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population …
Testing measurement invariance over time with intensive longitudinal data and identifying a source of non-invariance
E Kim, C Cao, S Liu, Y Wang… - … Equation Modeling: A …, 2023 - Taylor & Francis
Longitudinal measurement invariance (LMI) is a critical prerequisite to assessing change
over time with intensive longitudinal data (ILD). For LMI testing with ILD, we propose cross …
over time with intensive longitudinal data (ILD). For LMI testing with ILD, we propose cross …
Investigating the impact of covariate inclusion on sample size requirements of factor mixture modeling: A Monte Carlo simulation study
Factor mixture modeling (FMM) has been increasingly used in behavioral and social
sciences to capture underlying population heterogeneity. This Monte Carlo simulation study …
sciences to capture underlying population heterogeneity. This Monte Carlo simulation study …
A Factor Mixture Model for Item Responses and Certainty of Response Indices to identify student knowledge profiles
The certainty of response index (CRI) measures respondents' confidence level when
answering an item. In conjunction with the answers to the items, previous studies have used …
answering an item. In conjunction with the answers to the items, previous studies have used …
Combined approach to multi-informant data using latent factors and latent classes: Trifactor mixture model
E Kim, N von der Embse - Educational and Psychological …, 2021 - journals.sagepub.com
Although collecting data from multiple informants is highly recommended, methods to model
the congruence and incongruence between informants are limited. Bauer and colleagues …
the congruence and incongruence between informants are limited. Bauer and colleagues …
Brief Report: Polynomial Regression Mixture Modeling for Heterogeneous Effects of Informant Congruence
E Kim, N von der Embse - The Journal of Experimental Education, 2024 - Taylor & Francis
Using data from multiple informants has long been considered best practice in education.
However, multiple informants often disagree on similar constructs, complicating decision …
However, multiple informants often disagree on similar constructs, complicating decision …
DIF detection with zero-inflation under the factor mixture modeling framework
Response data containing an excessive number of zeros are referred to as zero-inflated
data. When differential item functioning (DIF) detection is of interest, zero-inflation can …
data. When differential item functioning (DIF) detection is of interest, zero-inflation can …
Mixed effects of item parceling on performance of factor mixture modeling
Factor mixture modeling (FMM) is generally complex with both unobserved categorical and
unobserved continuous variables. We explore the potential of item parceling to reduce the …
unobserved continuous variables. We explore the potential of item parceling to reduce the …