Hypothesis Testing and Model Comparison in Two-level Structural Equation Models
Bibliographic Data
| ID | 19291079 |
|---|---|
| Authors | Sik-Yum Lee, Sik‐yum Lee (Chinese University of Hong Kong), Xin-Yuan Song |
| Year | 2001 |
| Volume | 36 |
| Issue | 4 |
| Pages | 639-655 |
| Publication date | 2001-10-01 |
| Peer Reviewed | Yes |
| 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 | 10.1207/s15327906mbr3604_07 |
| PMID | 26822185 |
| OpenAlex | W1968438553 |
| Language | EN |
| Citations received | 4 |
| References cited | 35 |
One basic and important problem in two-level structural equation modeling is to find a good model for the observed sample data. This article demonstrates the use of the well-known Bayes factor in the Bayesian literature for hypothesis testing and model comparison in general two-level structural equation models. It is shown that the proposed methodology is flexible, and can be applied to situations with a wide variety of nonnested models. Moreover, some problems encountered in using existing methods for goodness-of-fit assessment of the proposed model can be alleviated. An illustrative example with some real data from an AIDS care study is presented
Bayes factor · Bayes' theorem · Bayesian probability · Data mining · Econometrics · Goodness of fit · Machine learning · Statistical hypothesis testing · Statistics · Structural equation modeling · Artificial Intelligence · Bayesian Modeling and Causal Inference · Computer Science · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference
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| Unique citing works | 4 |
|---|---|
| Citations per year | 0.19 |
| Citation span | 2005 - 2023 (19) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 4 |