Bayesian Measurement-Error-Driven Hidden Markov Regression Model for Calibrating the Effect of Covariates on Multistate Outcomes: Application to Androgenetic Alopecia
May 2018
in “
Statistics in Medicine
”
Studysummary This study found that the proposed Bayesian measurement-error-driven hidden Markov regression model effectively calibrated inflated covariate effect sizes in a community-based survey on androgenetic alopecia regardless of misclassification type.
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