Bayesian Analysis of Nonlinear Quantile Structural Equation Model with Possible Non-Ignorable Missingness
This paper develops a nonlinear quantile structural equation model via the Bayesian approach, aiming to more accurately analyze the relationships between latent variables, with special attention paid to the issue of non-ignorable missing data in the model. The model not only incorporates quantile re...
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| Hlavní autoři: | , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
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MDPI AG
2025-09-01
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| Edice: | Mathematics |
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| On-line přístup: | https://www.mdpi.com/2227-7390/13/19/3094 |
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