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

Survival analysis: A self-learning text (2nd ed.). K Beven, Environmental Modelling: An uncertain Future? Multilevel survival models are flexible and efficient tools in studying health inequalities of life expectancy or survival time data with a geographic structure of more than 2 levels. In an analysis of individuals' health inequality based on mortality, Gakidou [12] proposed a measure of total health inequality derived from the beta-binomial regression model, which unified treatment of various measures including the Gini coefficient [13] and other estimates of inequalities. Hosmer DW, Lemeshow S: Applied Survival Analysis: Regression Modeling of Time to Event Data. Applied survival Evaluation: Regression Modeling of Time to Occasion Information. The study of events involving an element of time has a long and important history in statistical study and practice. New York: Springer-Verlag; 2000:74. Survival analysis, also identified as event history evaluation, is a class of statistical methods for studying the occurrence and timing survival data have two attributes that are challenging to handle with other statistical methods: censoring and time-dependent covariates. Product DescriptionTHE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION Since. Applied survival analysis: Regression modeling of time to event data. Therneau TM, Grambsch PM: Modeling Survival Data: Extending the Cox Model. May, Applied Survival Analysis, Regression Modeling of Time-to-Event Data.