title: A joint model for longitudinal measurements and survival data in the presence of multiple failure types.
abstract: In this article we study a joint model for longitudinal measurements and competing risks survival data. Our joint model provides a flexible approach to handle possible nonignorable missing data in the longitudinal measurements due to dropout. It is also an extension of previous joint models with a single failure type, offering a possible way to model informatively censored events as a competing risk. Our model consists of a linear mixed effects submodel for the longitudinal outcome and a proportional cause-specific hazards frailty submodel (Prentice et al., 1978, Biometrics 34, 541-554) for the competing risks survival data, linked together by some latent random effects. We propose to obtain the maximum likelihood estimates of the parameters by an expectation maximization (EM) algorithm and estimate their standard errors using a profile likelihood method. The developed method works well in our simulation studies and is applied to a clinical trial for the scleroderma lung disease.
authors.affiliation: Department of Biostatistics, School of Public Health, University of California at Los Angeles, Los Angeles, California 90095, U.S.A.|Department of Biomathematics, University of California at Los Angeles, 10833 Leconte Avenue, Box 951766, Los Angeles, California 90095-1766, U.S.A.
authors.forename: Robert M
authors.initials: RM
authors.lastname: Elashoff
authors.affiliation: Department of Biostatistics, School of Public Health, University of California at Los Angeles, Los Angeles, California 90095, U.S.A.
authors.forename: Gang
authors.initials: G
authors.lastname: Li
authors.affiliation: Department of Biomathematics, University of California at Los Angeles, 10833 Leconte Avenue, Box 951766, Los Angeles, California 90095-1766, U.S.A.
authors.forename: Ning
authors.initials: N
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D003520:Cyclophosphamide / Q000627:therapeutic use; D003627:Data Interpretation, Statistical; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D008137:Longitudinal Studies; D008171:Lung Diseases / Q000188:drug therapy; D015233:Models, Statistical; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012595:Scleroderma, Systemic / Q000188:drug therapy; D016019:Survival Analysis
chemical_list: D003520:Cyclophosphamide