title: Predictive margins with survey data.
abstract: In the analysis of covariance, the display of adjusted treatment means allows one to compare mean (treatment) group outcomes controlling for different covariate distributions in the groups. Predictive margins are a generalization of adjusted treatment means to nonlinear models. The predictive margin for group r represents the average predicted response if everyone in the sample had been in group r. This paper discusses the use of predictive margins with complex survey data, where an important consideration is the choice of covariate distribution used to standardize the predictive margin. It is suggested that the textbook formula for the standard error of an adjusted treatment mean from the analysis of covariance may be inappropriate for applications involving survey data. Applications are given using data from the 1992 National Health Interview Survey (NHIS) and the Epidemiologic Followup Study to the first National Health and Nutrition Examination Survey (NHANES I).
authors.affiliation: Biostatistics Branch, National Cancer Institute, Bethesda, Maryland 20892, USA. BG1P@NIH.GOV
authors.forename: B I
authors.initials: BI
authors.lastname: Graubard
authors.forename: E L
authors.initials: EL
authors.lastname: Korn
mesh_terms: D000704:Analysis of Variance; D001699:Biometry; D003625:Data Collection / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D005260:Female; D006306:Health Surveys; D006801:Humans; D007348:Insurance, Health; D016015:Logistic Models; D008175:Lung Neoplasms / Q000453:epidemiology; D008297:Male; D009749:Nutrition Surveys; D012002:Rectal Diseases / Q000175:diagnosis; D016019:Survival Analysis