Goodness-of-fit methods for additive-risk models in tumorigenicity experiments.
In tumorigenicity experiments, a complication is that the time to event is generally not observed, so that the time to tumor is subject to interval censoring. One of the goals in these studies is to properly model the effect of dose on risk. Thus, it is important to have goodness of fit procedures available for assessing the model fit. While several estimation procedures have been developed for current-status data, relatively little work has been done on model-checking techniques. In this article, we propose numerical and graphical methods for the analysis of current-status data using the additive-risk model, primarily focusing on the situation where the monitoring times are dependent. The finite-sample properties of the proposed methodology are examined through numerical studies. The methods are then illustrated with data from a tumorigenicity experiment.
Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, Michigan 48109-2029, USA. ghoshd@umich.edu
Debashis
D
Ghosh
D000818:Animals; D001652:Bile Ducts / Q000187:drug effects / Q000473:pathology; D001699:Biometry; D002273:Carcinogens / Q000633:toxicity*; D005260:Female; D006965:Hyperplasia; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D009374:Neoplasms, Experimental / Q000139:chemically induced*; D011075:Polybrominated Biphenyls / Q000633:toxicity; D016016:Proportional Hazards Models; D051381:Rats; D012307:Risk Factors; D016019:Survival Analysis
D002273:Carcinogens; D011075:Polybrominated Biphenyls