A hidden Markov model approach to analyze longitudinal ternary outcomes when some observed states are possibly misclassified.

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A hidden Markov model approach to analyze longitudinal ternary outcomes when some observed states are possibly misclassified.

Benoit JS, Chan W, Luo S, Yeh HW, Doody R. A hidden Markov model approach to analyze longitudinal ternary outcomes when some observed states are possibly misclassified. Stat Med. 2016 Apr 30; 35(9):1549-57.

View in: PubMed

subject areas

Algorithms
Data Accuracy
Data Interpretation, Statistical
Early Diagnosis
Humans
Longitudinal Studies
Markov Chains
Models, Statistical
Time Factors
Treatment Outcome

authors with profiles

Hung-Wen Yeh