Baseline patient characteristics and mortality associated with longitudinal intervention compliance.
Lin et al. (http://www.biostatsresearch.com/upennbiostat/papers/, 2006) proposed a nested Markov compliance class model in the Imbens and Rubin compliance class model framework to account for time-varying subject noncompliance in longitudinal randomized intervention studies. We use superclasses, or latent compliance class principal strata, to describe longitudinal compliance patterns, and time-varying compliance classes are assumed to depend on the history of compliance. In this paper, we search for good subject-level baseline predictors of these superclasses and also examine the relationship between these superclasses and all-cause mortality. Since the superclasses are completely latent in all subjects, we utilize multiple imputation techniques to draw inferences. We apply this approach to a randomized intervention study for elderly primary care patients with depression.
Lin
Julia Y
JY
Center for Multicultural Mental Health Research, Somerville, MA 02143, USA. jlin@charesearch.org
Ten Have
Thomas R
TR
Bogner
Hillary R
HR
Elliott
Michael R
MR
D000368:Aged; D003866:Depressive Disorder / Q000401:mortality / Q000628:therapy; D006801:Humans; D008137:Longitudinal Studies; D008390:Markov Chains; D015233:Models, Statistical; D009026:Mortality; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D018579:Patient Selection; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic; D013997:Time Factors; D000092864:Suicide Prevention