Latent Variable Analysis With Categorical Outcomes : Multiple-Group And Growth Modeling In Mplus

By B. Muthén, T. Asparouhov, M. Muthén. 2002

475 citations recorded by the source corpus.

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Citations in the corpus

Applying Multigroup Confirmatory Factor Models for Continuous Outcomes to Likert Scale Data Complicates Meaningful Group Comparisons (2004, methodology): “In the other approach, the probability of choosing a certain response category conditional on the factor score is modeled directly (Agresti, 1990; Jöreskog & Moustaki, 2001; Muthén & Asparouhov, 2002).”
Measurement Invariance Conventions and Reporting: The State of the Art and Future Directions for Psychological Research (2016, methodology): “…items that are measured with two categories (binary) rather than on a continuous scale, metric and scalar invariance may be tested in a single step (Muthén & Asparouhov, 2002), and models intended to compare SEM-CFA to IRT methods may also report a combined metric-and-scalar invariance step…”
Conducting Measurement Invariance Tests with Ordinal Data: A Guide for Social Work Researchers (2015, background): “Many researchers consider partial measurement invariance acceptable if the proportion of noninvariant parameters to all parameters tested is small (Dimitrov, 2010; Millsap & Olivera-Alguilar, 2012; Muthén & Asparouhov, 2002; Sass, 2011).”
Comparison of Models for the Analysis of Intensive Longitudinal Data (2019, methodology): “mean zero) while that is not the case for the DSEM autoregressive equation (11).”
A Note on the Relation Between Factor Analytic and Item Response Theory Models (2008, methodology): “Several different parameterizations of the binary FA model have been described and implemented in recent years, as noted by Millsap and Yun-Tein (2004) and Muthén and Asparouhov (2002).”
The development of emotional and behavioral self-regulation and their effects on academic achievement in childhood (2018, background): “Compared with continuous data, the steps of longitudinal measurement invariance testing differ with categorical data because the factor loadings and thresholds must be varied in tandem (Muthén & Asparouhov, 2002).”
Testing Measurement Invariance: A Comparison of Multiple-Group Categorical CFA and IRT (2011, methodology): “…study, theta parameterization is optimal because the unique factor variances are freely estimated across multiple groups, so invariance of unique variances can be tested rather than assumed as in delta parameterization (Kamata & Bauer, 2008; Millsap & Yun-Tein, 2004; Muthén & Asparouhov, 2002).”
Assessing Internet Addiction Using the Parsimonious Internet Addiction Components Model—A Preliminary Study (2013, methodology): “Relationships between the Internet addiction components were assessed using polychoric correlations as the former were treated as ordered categorical rather than continuous (Muthén and Asparouhov 2002).”
Performance of Estimators for Confirmatory Factor Analysis of Ordinal Variables with Missing Data (2020, methodology): “The observed-data log-likelihood is logL ¼ Pn i¼1 log Li (e.g., Muthén & Asparouhov, 2002b), where Li is the likelihood function for individual i, which is simply the product of the conditional probabilities for the observed ordinal responses [i.e., Pðyi ¼ cjηiÞ] across indicator variables assuming…”
Testing Measurement Invariance Using MIMIC (2012, methodology): “The parameter values, the magnitude of DIF, and sample size were selected with the reference to the previous simulation studies on the similar research conditions (Kim & Yoon, 2011; Meade & Lautenschlager, 2004; Muthén & Asparouhov, 2002; Stark et al., 2006; Yoon, 2008; Yoon & Millsap, 2007).”
Evaluating Measurement Invariance of TALIS 2013 Complex Scales: Comparison between Continuous and Categorical Multiple-Group Confirmatory Factor Analyses (2014, methodology): “For ordered-categorical variables (e.g., four-point Likert-scale responses), Muthén and Asparouhov (2002) and Millsap and Yun-Tein (2004) proposed a categorical MGCFA approach with the solution for full measurement invariance.”
Multiple-Group Invariance with Categorical Outcomes Using Updated Guidelines: An Illustration Using Mplus and the lavaan/semTools Packages (2020, methodology): “Based on the work of Millsap (2011), Muthén and Christoffersson (1981), Muthén and Asparouhov (2002), and others, the methods of establishing ME/I for categorical observed variables are well established.”
Multiple-Group Confirmatory Factor Analysis in R--A Tutorial in Measurement Invariance with Continuous and Ordinal Indicators. (2014, methodology): “However, testing for strict invariance, i.e. testing the equality of residual variances, is only possible when theta-parameterization is used to identify model parameters (Muthén & Asparouhov, 2002).”
Consequences of Parental Divorce for Adult Children’s Support of Their Frail Parents (2008, background): “…variables are allowed to vary across time, and the scale factors (i.e., the inverse of the conditional standard deviations of the latent response variable at each time point) are fixed at 1 at the first time point and freely estimated for the remaining time points (Muthén & Asparouhov, 2002).”
Assessing Factorial Invariance in Ordered-Categorical Measures (2004, methodology): “For Mplus, we have 2pc independent response proportions across variables and groups.”
When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. (2012, background): “However, these two sets of assumptions are mathematically equivalent (B. O. Muthén & Asparouhov, 2002; Takane & de Leeuw, 1987; Wirth & Edwards, 2007).”
Measurement Invariance in International Surveys: Categorical Indicators and Fit Measure Performance (2017, methodology): “…models is less widely discussed than the single group case; however, based on the work of Millsap as well as Muthén and Chistoffersson (1981), Muthén and Asparouhov (2002), and others, the methods for establishing measurement invariance in the case of categorical observed variables is…”
Testing Measurement Invariance in Longitudinal Data with Ordered-Categorical Measures (2016, unknown): “12 For ordered-categorical CFA models, two parameterizations are available: delta and theta (Muthén & Asparouhov, 2002).”
Relative Performance of Categorical Diagonally Weighted Least Squares and Robust Maximum Likelihood Estimation (2014, methodology): “This study focuses on cat-WLS estimation for categorical outcomes as described by Muthén and Asparouhov (2002) based on the so-called latent response variable formulation.”
Evaluating Model Fit With Ordered Categorical Data Within a Measurement Invariance Framework: A Comparison of Estimators (2014, background): “For more detail on why the metric and scalar should be constrained in tandem see Muthén and Asparouhov (2002).”