Case-cohort methods for survival data on families from routine registers.
In the Nordic countries, there exist several registers containing information on diseases and risk factors for millions of individuals. This information can be linked to families by the use of personal identification numbers, and represents a great opportunity for studying diseases that show familial aggregation. Due to the size of the registers, it is difficult to analyze the data by using traditional methods for multivariate survival analysis, such as frailty or copula models. Since the size of the cohort is known, case-cohort methods based on pseudo-likelihoods are suitable for analyzing the data. We present methods for sampling control families both with and without replacement, and with or without stratification. The data are stratified according to family size and covariate values. Depending on the sampling method, results from simulations indicate that one only needs to sample 1-5 per cent of the control families in order to obtain good efficiency compared with a traditional cohort analysis. We also provide an application to survival data from the Medical Birth Registry of Norway.
Moger
Tron Anders
TA
Institute of Basic Medical Sciences, Department of Biostatistics, University of Oslo, Blindern, 0317 Oslo, Norway. tronmo@medisin.uio.no
Pawitan
Yudi
Y
Borgan
Ornulf
O
D016022:Case-Control Studies; D015331:Cohort Studies; D003198:Computer Simulation; D005192:Family Health; D006801:Humans; D007226:Infant Mortality; D007231:Infant, Newborn; D015233:Models, Statistical; D009099:Multiple Birth Offspring / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D009664:Norway / Q000453:epidemiology; D012042:Registries / Q000706:statistics & numerical data*; D012107:Research Design; D016019:Survival Analysis; D013548:Sweden / Q000453:epidemiology