Score and deviance residuals based on the full likelihood approach in survival analysis.
Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, USA.
Department of Mathematics and Statistics, Old Dominion University, Norfolk, Virginia, USA.
Biostatics and Bioinformatics Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Rockville, Maryland, USA.
- Published Article
- Publication Date
Nov 01, 2020
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. © 2020 John Wiley & Sons Ltd.
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The corresponding record at NLM can be accessed at https://www.ncbi.nlm.nih.gov/pubmed/32776412