Semiparametric Proportional Hazards Regression with Fixed Covariates

  • John P. Klein
  • Melvin L. Moeschberger
Part of the Statistics for Biology and Health book series (SBH)


Often one is interested in comparing two or more groups of times-toevent. If the groups are similar, except for the treatment under study, then, the nonparametric methods of Chapter 7 may be used directly. More often than not, the subjects in the groups have some additional characteristics that may affect their outcome. For example, subjects may have demographic variables recorded, such as age, gender, socioeconomic status, or education; behavioral variables, such as dietary habits, smoking history, physical activity level, or alcohol consumption; or physiological variables, such as blood pressure, blood glucose levels, hemoglobin levels, or heart rate. Such variables may be used as covariates (explanatory variables, confounders, risk factors, independent variables) in explaining the response (dependent) variable. After adjustment for these potential explanatory variables, the comparison of survival times between groups should be less biased and more precise than a simple comparison.


Likelihood Ratio Test Hazard Rate Survival Function Wald Test Local Test 
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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • John P. Klein
    • 1
  • Melvin L. Moeschberger
    • 2
  1. 1.Division of BiostatisticsMedical College of WisconsinMilwaukeeUSA
  2. 2.School of Public Health, Division of Epidemiology and BiometricsThe Ohio State University Medical CenterColumbusUSA

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