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A Gibbs sampler for the multidimensional fourāparameter logistic item response model via a data augmentation scheme
- Source :
- British Journal of Mathematical and Statistical Psychology. 74:427-464
- Publication Year :
- 2021
- Publisher :
- Wiley, 2021.
-
Abstract
- The four-parameter logistic (4PL) item response model, which includes an upper asymptote for the correct response probability, has drawn increasing interest due to its suitability for many practical scenarios. This paper proposes a new Gibbs sampling algorithm for estimation of the multidimensional 4PL model based on an efficient data augmentation scheme (DAGS). With the introduction of three continuous latent variables, the full conditional distributions are tractable, allowing easy implementation of a Gibbs sampler. Simulation studies are conducted to evaluate the proposed method and several popular alternatives. An empirical data set was analysed using the 4PL model to show its improved performance over the three-parameter and two-parameter logistic models. The proposed estimation scheme is easily accessible to practitioners through the open-source IRTlogit package.
- Subjects :
- Statistics and Probability
Scheme (programming language)
Response model
Computer science
Latent variable
01 natural sciences
Set (abstract data type)
010104 statistics & probability
symbols.namesake
0504 sociology
Arts and Humanities (miscellaneous)
Computer Simulation
0101 mathematics
General Psychology
computer.programming_language
Models, Statistical
05 social sciences
050401 social sciences methods
Bayes Theorem
General Medicine
Conditional probability distribution
Deviance information criterion
Logistic Models
symbols
Asymptote
computer
Algorithm
Algorithms
Gibbs sampling
Subjects
Details
- ISSN :
- 20448317 and 00071102
- Volume :
- 74
- Database :
- OpenAIRE
- Journal :
- British Journal of Mathematical and Statistical Psychology
- Accession number :
- edsair.doi.dedup.....17023fd55b3a46ceab540c0084db4994