Titlebook: Survival Analysis; A Self-Learning Text David G. Kleinbaum,Mitchel Klein Textbook 2012Latest edition Springer Science+Business Media, LLC,

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書目名稱Survival Analysis影響因子(影響力)




書目名稱Survival Analysis影響因子(影響力)學(xué)科排名




書目名稱Survival Analysis網(wǎng)絡(luò)公開度




書目名稱Survival Analysis網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Survival Analysis被引頻次




書目名稱Survival Analysis被引頻次學(xué)科排名




書目名稱Survival Analysis年度引用




書目名稱Survival Analysis年度引用學(xué)科排名




書目名稱Survival Analysis讀者反饋




書目名稱Survival Analysis讀者反饋學(xué)科排名

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Introduction to Survival Analysis, type of problem addressed by survival analysis, the outcome variable considered, the need to take into account “censored data,” what a survival function and a hazard function represent, basic data layouts for a survival analysis, the goals of survival analysis, and some examples of survival analysis.

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Evaluating the Proportional Hazards Assumption,We begin with a brief review of the characteristics of the Cox proportional hazards (PH) model. We then give an overview of three methods for checking the PH assumption: graphical, goodness-of-fit (GOF), and time-dependent variable approaches.

GRILL

The Stratified Cox Procedure,We begin with an example of the use of the stratified Cox procedure for a single predictor that does not satisfy the PH assumption. We then describe the general approach for fitting a stratified Cox model, including the form of the (partial) likelihood function used to estimate model parameters.

EXCEL

Extension of the Cox Proportional Hazards Model for Time-Dependent Variables,We begin by defining a time-dependent variable and providing some examples of such a variable. We also state the general formula for a Cox model that is extended to allow time dependent variables, followed by a discussion of the characteristics of this model, including a description of the hazard ratio.

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