LEADER 05828nam 2200805 450 001 9910130964503321 005 20210209180536.0 010 $a1-283-28250-X 010 $a9786613282507 010 $a0-470-25801-2 010 $a0-470-25800-4 035 $a(CKB)3460000000080824 035 $a(EBL)700085 035 $a(OCoLC)794326228 035 $a(SSID)ssj0000554362 035 $a(PQKBManifestationID)11344515 035 $a(PQKBTitleCode)TC0000554362 035 $a(PQKBWorkID)10512763 035 $a(PQKB)11137745 035 $a(MiAaPQ)EBC700085 035 $a(MiAaPQ)EBC4026396 035 $a(Au-PeEL)EBL4026396 035 $a(CaPaEBR)ebr11104250 035 $a(OCoLC)927495016 035 $a(PPN)167569430 035 $a(EXLCZ)993460000000080824 100 $a20160819h20082008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aApplied survival analysis $eregression modeling of time-to-event data /$fDavid W. Hosmer, Stanley Lemeshow, Susanne May /$fDavid W. Hosmer, Stanley Lemeshow, Susanne May 205 $a2nd ed. 210 1$aHoboken, New Jersey :$cWiley-Interscience,$d2008 210 4$dİ2008 215 $a1 online resource (418 p.) 225 1 $aWiley Series in Probability and Statistics 300 $aDescription based upon print version of record 311 $a0-471-75499-4 320 $aIncludes bibliographical references and index 327 $aApplied Survival Analysis: Regression Modeling of Time-to-Event Data; Contents; Preface; 1 Introduction to Regression Modeling of Survival Data; 1.1 Introduction; 1.2 Typical Censoring Mechanisms; 1.3 Example Data Sets; Exercises; 2 Descriptive Methods for Survival Data; 2.1 Introduction; 2.2 Estimating the Survival Function; 2.3 Using the Estimated Survival Function; 2.4 Comparison of Survival Functions; 2.5 Other Functions of Survival Time and Their Estimators; Exercises; 3. Regression Models for Survival Data; 3.1 Introduction; 3.2 Semi-Parametric Regression Models 327 $a3.3 Fitting the Proportional Hazards Regression Model3.4 Fitting the Proportional Hazards Model with Tied Survival Times; 3.5 Estimating the Survival Function of the Proportional Hazards Regression Model; Exercises; 4. Interpretation of a Fitted Proportional Hazards Regression Model; 4.1 Introduction; 4.2 Nominal Scale Covariate; 4.3 Continuous Scale Covariate; 4.4 Multiple-Covariate Models; 4.5 Interpreting and Using the Estimated Covariate-Adjusted Survival Function; Exercises; 5. Model Development; 5.1 Introduction; 5.2 Purposeful Selection of Covariates 327 $a5.2.1 Methods to examine the scale of continuous covariates in the log hazard5.2.2 An example of purposeful selection of covariates; 5.3 Stepwise, Best-Subsets and Multivariable Fractional PolynomialMethods of Selecting Covariates; 5.3.1 Stepwise selection of covariates; 5.3.2 Best subsets selection of covariates; 5.3.3 Selecting covariates and checking their scale using multivariable fractional polynomials; 5.4 Numerical Problems; Exercises; 6. Assessment of Model Adequacy; 6.1 Introduction; 6.2 Residuals; 6.3 Assessing the Proportional Hazards Assumption 327 $a6.4 Identification of Influential and Poorly Fit Subjects6.5 Assessing Overall Goodness-of-Fit; 6.6 Interpreting and Presenting Results From the Final Model; Exercises; 7. Extensions of the Proportional Hazards Model; 7.1 Introduction; 7.2 The Stratified Proportional Hazards Model; 7.3 Time-Varying Covariates; 7.4 Truncated, Left Censored and Interval Censored Data; Exercises; 8. Parametric Regression Models; 8.1 Introduction; 8.2 The Exponential Regression Model; 8.3 The Weibull Regression Model; 8.4 The Log-Logistic Regression Model; 8.5 Other Parametric Regression Models; Exercises 327 $a9. Other Models and Topics9.1 Introduction; 9.2 Recurrent Event Models; 9.3 Frailty Models; 9.4 Nested Case-Control Studies; 9.5 Additive Models; 9.6 Competing Risk Models; 9.7 Sample Size and Power; 9.8 Missing Data; Exercises; Appendix 1 The Delta Method; Appendix 2 An Introduction to the Counting Process Approach to Survival Analysis; Appendix 3 Percentiles for Computation of the Hall and Wellner Confidence Band; References; Index 330 $aTHE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA-NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edi 410 0$aWiley series in probability and statistics 606 $aMedicine$xResearch$xStatistical methods 606 $aMedical sciences$xStatistical methods$xComputer programs 606 $aRegression analysis$xData processing 606 $aPrognosis$xStatistical methods 606 $aLogistic distribution 615 0$aMedicine$xResearch$xStatistical methods. 615 0$aMedical sciences$xStatistical methods$xComputer programs. 615 0$aRegression analysis$xData processing. 615 0$aPrognosis$xStatistical methods. 615 0$aLogistic distribution. 676 $a610.72 676 $a610.727 700 $aHosmer$b David W.$0251740 702 $aLemeshow$b Stanley 702 $aMay$b Susanne 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910130964503321 996 $aApplied survival analysis$92031066 997 $aUNINA