research Bayesian measurement-error-driven hidden Markov regression model for calibrating the effect of covariates on multistate outcomes: Application to androgenetic alopecia
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.

