商品簡介
Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard pre-calculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics. The authors emphasize parametric log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of left-truncated and right-censored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s). In a chapter written by Stephen Portnoy, censored regression quantiles - a new nonparametric regression methodology (2003) - is developed to identify important forms of population heterogeneity and to detect departures from traditional Cox models. By generalizing the Kaplan-Meier estimator to regression models for conditional quantiles, this methods provides a valuable complement to traditional Cox proportional hazards approaches.
目次
INTRODUCTIONMotivation - Two Examples Basic definitionsCensoring and Truncation Models Course ObjectivesData entry and Import/Export of Data FilesExercisesNONPARAMETRIC METHODSKaplan-Meier Estimator of SurvivalComparison of Survivor Curves: Two-Sample ProblemExercisesPARAMETRIC METHODSFrequently Used (Continuous) ModelsMaximum Likelihood Estimation (MLE)Confidence Intervals and TestsOne-Sample ProblemTwo-Sample ProblemA Bivariate Version of the Delta MethodThe Delta Method for a Bivariate Vector FieldGeneral Version of the Likelihood Ratio TestExercisesREGRESSION MODELSExponential Regression ModelWeibull Regression ModelCox Proportional Hazards (PH) ModelAccelerated Failure Time ModelSummaryAIC procedure for Variable SelectionExercisesTHE COX PROPORTIONAL HAZARDS MODELAIC Procedure for Variable SelectionStratified Cox PH RegressionExercisesReview of First Five Chapters: Self-EvaluationMODEL CHECKING: DATA DIAGNOSTICSBasic graphical MethodsWeibull Regression ModelCox proportional Hazards ModelExercisesADDITIONAL TOPICSExtended Cox ModelCompeting Risks: Cumulative Incidence EstimatorAnalysis of Left-Truncated and Right-Censored DataExercisesCENSORED REGRESSION QUANTILES, by Stephen PortnoyIntroductionWhat are Regression Quantiles?Computation of Censored Regression QuantilesExamples of Censored Regression QuantileExercisesREFERENCESINDEX
