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Applied Survival Analysis: Regression Modeling of Time to Event Data David W. Hosmer, Stanley Lemeshow
Publisher: Wiley-Interscience

1997 Applied structural mechanics : fundamentals of elasticity, load-bearing structures, structural optimization Eschenauer H. Survival analysis: A self-learning text (2nd ed.). 8 Incidence and Reoccurrence of Damage. Regression modelling of mortality and time to death data. Applied Logistic Regression Modeling of Time to Event Data - FC2David W. 14 Growth in Cross-Sectional Area of Surviving Trees. Regression Methods in Biostatistics - Linear, Logistic , Survival, and . 8 Severity and Consequences of Damage. Applied Regression Analysis (Wiley Series in Probability and . Applied survival analysis: Regression modeling of time to event data. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. Table S4 lists data for multivariate Cox regression analysis with selected clinical parameters – ER status based on immunohistochemistry, LN status (positive versus negative), histological grading (Elston Ellis I, II and III) – tumor size and the output of . Horizontal axis, time at which right censoring was applied to all samples; vertical axis, -log(P value) of the log-rank test from the Kaplan–Meier analysis for a given time-censoring and a particular signature with DMFS as the endpoint. Our analysis of survival time used an “accelerated failure-time regression model” to quantify the effect of independent variables on the distribution of survival times (Allison 1995, Hosmer and Lemeshow 1999). Effects on acute prognosis were either evaluated by analyzing ICU mortality or time to death after inclusion.