A latent autoregressive model for longitudinal binary data subject to informative missingness.
Longitudinal clinical trials often collect long sequences of binary data. Our application is a recent clinical trial in opiate addicts that examined the effect of a new treatment on repeated binary urine tests to assess opiate use over an extended follow-up. The dataset had two sources of missingness: dropout and intermittent missing observations. The primary endpoint of the study was comparing the marginal probability of a positive urine test over follow-up across treatment arms. We present a latent autoregressive model for longitudinal binary data subject to informative missingness. In this model, a Gaussian autoregressive process is shared between the binary response and missing-data processes, thereby inducing informative missingness. Our approach extends the work of others who have developed models that link the various processes through a shared random effect but do not allow for autocorrelation. We discuss parameter estimation using Monte Carlo EM and demonstrate through simulations that incorporating within-subject autocorrelation through a latent autoregressive process can be very important when longitudinal binary data is subject to informative missingness. We illustrate our new methodology using the opiate clinical trial data.
Albert
Paul S
PS
Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA. albertp@ctep.nci.nih.gov
Follmann
Dean A
DA
Wang
Shaohua A
SA
Suh
Edward B
EB
D000465:Algorithms; D001699:Biometry; D002047:Buprenorphine / Q000627:therapeutic use; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D006801:Humans; D008137:Longitudinal Studies; D008691:Methadone / Q000627:therapeutic use; D015233:Models, Statistical; D009010:Monte Carlo Method; D009294:Narcotics / Q000652:urine; D009293:Opioid-Related Disorders / Q000534:rehabilitation / Q000652:urine; D012044:Regression Analysis
D009294:Narcotics; D002047:Buprenorphine; D008691:Methadone