Evaluating Measurement Invariance in Categorical Data Latent Variable Models with the EPC-Interest
Datos Bibliográficos
| ID | 7971063 |
|---|---|
| Autores | Daniel L Oberski (0000-0001-7467-2297, Tilburg University), Jeroen K Vermunt (0000-0001-9053-9330), Guy B D Moors |
| Año | 2015 |
| Volumen | 23 |
| Número | 4 |
| Páginas | 550-563 |
| Fecha de publicación | 2015-01-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Political Analysis (JOURNAL) |
| Identificadores de la revista | ISSN: 1047-1987 • E-ISSN: 1476-4989 |
| Editorial | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1093/pan/mpv020 |
| OpenAlex | W2179772789 |
| Idioma | EN |
| Citas recibidas | 4 |
| Referencias citadas | 28 |
Many variables crucial to the social sciences are not directly observed but instead are latent and measured indirectly. When an external variable of interest affects this measurement, estimates of its relationship with the latent variable will then be biased. Such violations of “measurement invariance” may, for example, confound true differences across countries in postmaterialism with measurement differences. To deal with this problem, researchers commonly aim at “partial measurement invariance” that is, to account for those differences that may be present and important. To evaluate this importance directly through sensitivity analysis, the “EPC-interest” was recently introduced for continuous data. However, latent variable models in the social sciences often use categorical data. The current paper therefore extends the EPC-interest to latent variable models for categorical data and demonstrates its use in example analyses of U.S. Senate votes as well as respondent rankings of postmaterialism values in the World Values Study
Categorical variable · Confirmatory factor analysis · Econometrics · European Social Survey · Latent class model · Latent variable · Latent variable model · Local independence · Measurement invariance · Political science · Respondent · Statistics · Structural equation modeling · Variable (mathematics · Variables · Computer Science · Cultural Differences and Values · Mathematics · Sensory Analysis and Statistical Methods
Item bias and item response theory
Measurement invariance
Testing Structural Equation Models or Detection of Misspecifications?
Generalized Multilevel Structural Equation Modeling
Latent Variables in Psychology and the Social Sciences
A Review and Synthesis of the Measurement Invariance Literature
Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance
Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance
Controlling the False Discovery Rate
Measurement Invariance, Factor Analysis and Factorial Invariance
Fit indices in covariance structure modeling
Testing Structural Equation Models
Testing for the equivalence of factor covariance and mean structures
Evaluating Sensitivity of Parameters of Interest to Measurement Invariance in Latent Variable Models
Assessing Measurement Invariance in Cross‐National Consumer Research
A Latent Class Analysis of Tolerance for Nonconformity in the American Public
Changing Mass Priorities
A Spatial Model for Legislative Roll Call Analysis
The Simultaneous Decision(s) about the Number of Lower- and Higher-Level Classes in Multilevel Latent Class Analysis
Post-Materialism in an Environment of Insecurity
Gender Equality and Democracy
Heterogeneity in Post-materialist Value Priorities. Evidence from a Latent Class Discrete Choice Approach
| Obras citantes distintas | 4 |
|---|---|
| Citas por año | 0,57 |
| Intervalo de citas | 2019 - 2024 (6) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 4 |