论文信息 - Using SAS to calculate the Kent and O'Quigley measure of dependence for Cox proportional hazards regression model

Using SAS to calculate the Kent and O'Quigley measure of dependence for Cox proportional hazards regression model

Kent and O'Quigley (1988) apply the concept of information gain to define a measure of dependence (R-squared measure) between explanatory variables and a censored response variable within the framework of the Cox model. Two SAS macros to calculate this measure are presented. The first one is based on a Newton-Raphson search and makes use of the SAS IML procedure. The second one is a simple grid search using SAS DATA steps and Base-SAS procedures.

Harald Heinzl | H. Heinzl

[1] J. Kent. Information gain and a general measure of correlation , 1983 .

[2] R. A. Leibler,et al. On Information and Sufficiency , 1951 .

[3] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.

[4] J. Kalbfleisch,et al. The Statistical Analysis of Failure Time Data , 1980 .

[5] John T. Kent,et al. Measures of dependence for censored survival data , 1988 .

[6] J Stare,et al. Explained variation in survival analysis. , 1996, Statistics in medicine.

[7] David R. Cox,et al. Regression models and life tables (with discussion , 1972 .