Assessment of fit of the time-varying dynamic partial credit model using the posterior predictive model checking method.
Br J Math Stat Psychol
; 77(3): 532-552, 2024 Nov.
Article
en En
| MEDLINE
| ID: mdl-38379504
ABSTRACT
Several new models based on item response theory have recently been suggested to analyse intensive longitudinal data. One of these new models is the time-varying dynamic partial credit model (TV-DPCM; Castro-Alvarez et al., Multivariate Behavioral Research, 2023, 1), which is a combination of the partial credit model and the time-varying autoregressive model. The model allows the study of the psychometric properties of the items and the modelling of nonlinear trends at the latent state level. However, there is a severe lack of tools to assess the fit of the TV-DPCM. In this paper, we propose and develop several test statistics and discrepancy measures based on the posterior predictive model checking (PPMC) method (PPMC; Rubin, The Annals of Statistics, 1984, 12, 1151) to assess the fit of the TV-DPCM. Simulated and empirical data are used to study the performance of and illustrate the effectiveness of the PPMC method.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Psicometría
/
Simulación por Computador
/
Modelos Estadísticos
Límite:
Humans
Idioma:
En
Revista:
Br J Math Stat Psychol
/
Br. j. math. stat. psychol
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British journal of mathematical and statistical psychology
Año:
2024
Tipo del documento:
Article
País de afiliación:
Países Bajos