Semiparametric proportional means model for marker data contingent on recurrent event.
In many biomedical studies with recurrent events, some markers can only be measured when events happen. For example, medical cost attributed to hospitalization can only incur when patients are hospitalized. Such marker data are contingent on recurrent events. In this paper, we present a proportional means model for modelling the markers using the observed covariates contingent on the recurrent event. We also model the recurrent event via a marginal rate model. Estimating equations are constructed to derive the point estimators for the parameters in the proposed models. The estimators are shown to be asymptotically normal. Simulation studies are conducted to examine the finite-sample properties of the proposed estimators and the proposed method is applied to a data set from the Vitamin A Community Trial.
Cai
Jianwen
J
Department of Biostatistics, University of North Carolina at Chapel Hill, Campus Box 7420, Chapel Hill, NC, 27599-7420, USA. cai@bios.unc.edu
Zeng
Donglin
D
Pan
Wenqin
W
D015415:Biomarkers / Q000032:analysis*; D001938:Brazil; D002675:Child, Preschool; D003967:Diarrhea / Q000503:physiopathology; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012008:Recurrence; D018709:Statistics, Nonparametric; D014801:Vitamin A / Q000008:administration & dosage; D014802:Vitamin A Deficiency / Q000150:complications
D015415:Biomarkers; D014801:Vitamin A