Bayesian Nonparametric Latent Class Analysis for Different Item Types
Bibliographic Data
| ID | 19290964 |
|---|---|
| Authors | Meng Qiu (0009-0009-3897-7347, University of Notre Dame, corresponding author), Sally Paganin (0000-0002-3451-1795, Harvard University), Ilsang Ohn (0000-0003-3953-5953, Inha University), Lizhen Lin (0009-0001-9712-9681, University of Notre Dame) |
| Year | 2023 |
| Volume | 58 |
| Issue | 1 |
| Pages | 156-157 |
| Publication date | 2023-01-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Multivariate Behavioral Research (JOURNAL) |
| Journal identifiers | ISSN: 0027-3171 • E-ISSN: 1532-7906 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00273171.2022.2160958 |
| PMID | 36732314 |
| OpenAlex | W4318937764 |
| Language | EN |
| References cited | 2 |
Latent class analysis (LCA) is a popular statistical method used to group individuals into homogeneous subpopulations based on the responses to a set of variables. In the conventional LCA, the numb
Bayesian inference · Bayesian probability · Bayesian statistics · Class (philosophy) · Econometrics · Item response theory · Latent class model · Latent variable · Latent variable model · Machine learning · Multivariate analysis · Multivariate statistics · Nonparametric statistics · Psychometrics · Statistics · Artificial Intelligence · Computer Science · Genetic and phenotypic traits in livestock · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference
| Highly cited | No |
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