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- W97801399 abstract "Abstract A maximum likelihood (ML) approach for analyzing a multisample structural equation model with missing ordered categorical outcomes is introduced. In the ML estimation, the observed data are augmented with the real missing data and the hypothetical missing data that involve the latent variables and the unobserved continuous responses underlying the ordered categorical data. The resulting problem is handled by the implementation of a Monte Carlo EM algorithm to produce ML estimates of the unknown parameters. A path sampling procedure is proposed to compute the complicated observed-data log-likelihood, and eventually the Bayesian information criterion for model comparison and hypothesis testing. The proposed methodologies are used to analyze a two-sample quality of life (QOL) data set to investigate the similarities and differences of QOL between people in Western countries and in China." @default.
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- W97801399 date "2007-01-01" @default.
- W97801399 modified "2023-09-28" @default.
- W97801399 title "Analysis of Multisample Structural Equation Models with Applications to Quality of Life Data" @default.
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