Latent time-varying factors in longitudinal analysis: a linear mixed hidden Markov model for heart rates

• Published in: Statistics in medicine Vol. 33; no. 23; pp. 4116 - 4134
• Main Authors: Lagona, Francesco, Jdanov, Dmitri, Shkolnikova, Maria
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 15.10.2014; Wiley Subscription Services, Inc
• Subjects: Age Distribution; Aged; Aged, 80 and over; Aging - physiology; Aging - psychology; Algorithms; Biomarkers; Cardiovascular system; Comorbidity; EM algorithm; Female; Health Status; Heart Diseases - epidemiology; Heart Rate; hidden Markov model; Humans; Likelihood Functions; linear mixed model; Linear Models; longitudinal data; Longitudinal Studies; Male; Markov analysis; Markov Chains; Medical statistics; Middle Aged; Russia - epidemiology; Sex Distribution; Stress, Psychological - epidemiology; Stress, Psychological - physiopathology; Time Factors; Russia; heart rate; hidden Markov model; linear mixed model; EM algorithm; longitudinal data
• ISSN: 0277-6715; 1097-0258; 1097-0258
• DOI: 10.1002/sim.6220

Longitudinal data are often segmented by unobserved time‐varying factors, which introduce latent heterogeneity at the observation level, in addition to heterogeneity across subjects. We account for this latent structure by a linear mixed hidden Markov model. It integrates subject‐specific random eff...