Estimation of absolute risk from nested case-control data.
Benichou and Gail (1995, Biometrics 51, 182-194) describe methods for estimating the absolute risk of developing disease given a set of covariate values over a specified time interval from a case-control study within a cohort. The methods are most suitable for unmatched case-control studies, and are restricted to categorical covariates. Expanding on methods for estimating relative mortality from nested case-control studies presented in Borgan and Langholz (1993, Biometrics 49, 593-602), we present methods for estimating absolute risk from individually matched nested case-control data. These methods accommodate continuous and time-dependent covariate histories, the sampling of cases, and various control sampling designs.
Langholz
B
B
Department of Preventive Medicine, University of Southern California, School of Medicine, Los Angeles 90033, USA.
Borgan
O
O
D000328:Adult; D000368:Aged; D001699:Biometry / Q000379:methods*; D016022:Case-Control Studies; D015331:Cohort Studies; D003120:Colorado / Q000453:epidemiology; D003627:Data Interpretation, Statistical; D006801:Humans; D008175:Lung Neoplasms / Q000209:etiology / Q000401:mortality; D008297:Male; D008875:Middle Aged; D008906:Mining; D009381:Neoplasms, Radiation-Induced / Q000209:etiology / Q000401:mortality; D009784:Occupational Diseases / Q000209:etiology / Q000401:mortality; D016273:Occupational Exposure; D016016:Proportional Hazards Models; D011886:Radon / Q000009:adverse effects; D012306:Risk; D014501:Uranium / Q000009:adverse effects
D014501:Uranium; D011886:Radon