MCMCINLA Estimation of Missing Data and Its Application to Public Health Development in China in the Post-Epidemic Era

MCMCINLA Estimation of Missing Data and Its Application to Public Health Development in China in the Post-Epidemic Era

Medical data are often missing during epidemiological surveys and clinical trials. In this paper, we propose the MCMCINLA estimation method to account for missing data. We introduce a new latent class into the spatial lag model (SLM) and use a conditional autoregressive specification (CAR) spatial m...

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Bibliographic Details
Main Authors: Ding, S. (Author), Hu, X. (Author), Shi, X. (Author), Teng, J. (Author), Zhang, H. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
INLA
MCMC
missing data
public health
spatial lag model
Online Access:View Fulltext in Publisher

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