ANALYSIS OF GENERALIZED RESIDUALS IN HAZARD REGRESSION-MODELS

In the present paper, we consider a counting process and a model of it s intensity. We introduce the generalized residuals measuring the devi ation of observed times to counts from the expected times given by the model. These residuals are then used for assessing the goodness-of-fi t of hazard regression models. The method is inspired by Arjas' [4] gr aphical procedure (dealing with Cox's model) and generalized to a quit e general hazard regression case. The large sample properties of the t est statistics are derived, they are then specified for the case of Aa len's regression model. The diagnostic ability of the method is illust rated by an example with simulated data.