Dispersion tests and adjustments for survival and case-control studies.
Cox and Snell have pointed out that when the empirical variance of a measured response y is quite different from its nominal variance under an assumed probability model, standard errors that are not adjusted for the discrepancy may yield misleading inferences. This article describes a test for assessing departures from nominal dispersion in survival analysis and case-control studies. Also, a robust procedure for adjusting standard errors for these models is given.
Smith
P J
PJ
Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA 30341-3724.
D016022:Case-Control Studies; D016889:Endometrial Neoplasms / Q000401:mortality; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000401:mortality; D008297:Male; D015233:Models, Statistical; D016016:Proportional Hazards Models; D012307:Risk Factors; D016019:Survival Analysis