Score and deviance residuals based on the full likelihood approach in survival analysis.

Assuming the proportional hazards model and non-informative censoring, the full likelihood approach is used to obtain two new residuals. The first residual is based on the ideas used in obtaining score-type residuals similar to the partial likelihood approach. The second type of residual is based on the concept of deviance residuals. Extensive simulations are conducted to compare the performance of the residuals from the full likelihood-based approach with those of the partial likelihood method. We demonstrate through simulation studies that the full likelihood-based residuals are more efficient than their partial likelihood counterpart in identifying potential outliers when the censoring proportion is high. The graphical techniques are used to illustrate the applications of these residuals using some examples.

Duke Scholars

Author Susan Halabi Biostatistics & Bioinformatics, Division of Biostatistics

Author Yuan Wu Biostatistics & Bioinformatics, Division of Biostatistics