An introduction to survival analysis using Stata:
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| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
College Station, Texas
Stata Press
[2016]
|
| Edition: | Revised third edition |
| Series: | A Stata Press publication
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xxx, 428 Seiten Diagramme |
| ISBN: | 9781597181747 1597181749 |
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MARC
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Record in the Search Index
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| adam_text | Titel: An introduction to survival analysis using stata
Autor: Cleves, Mario Alberto
Jahr: 2016
Contents List of tables xiii List of figures xv Preface to the Revised Third Edition xix Preface to the Third Edition xxi Preface to the Second Edition xxiii Preface to the Revised Edition xxv Preface to the First Edition xxvii Notation and typography xxix 1 The problem of survival analysis 1 1.1 Parametric modeling........................... 2 1.2 Semiparametric modeling........................ 2 1.3 Nonparametric analysis ......................... 5 1.4 Linking the three approaches...................... 5 2 Describing the distribution of failure times 7 2.1 The survivor and hazard functions................... 7 2.2 The quantile function........................... 10 2.3 Interpreting the cumulative hazard and hazard rate.......... 13 2.3.1 Interpreting the cumulative hazard.............. 13 2.3.2 Interpreting the hazard rate.................. 15 2.4 Means and medians............................ 16 3 Hazard models 19 3.1 Parametric models............................ 20 3.2 Semiparametric models.......................... 21 3.3 Analysis time (time at risk)....................... 24
29 30 32 34 34 34 35 36 37 37 40 44 47 48 51 51 52 55 57 59 62 65 67 70 73 73 76 77 78 Censoring and truncation 4.1 Censoring.......................... 4.1.1 Right-censoring .................. 4.1.2 Interval-censoring................. 4.1.3 Left-censoring ................... 4.2 Truncation.......................... 4.2.1 Left-truncation (delayed entry) ......... 4.2.2 Right-truncation ................. 4.2.3 Gaps........................ Recording survival data 5.1 The desired format..................... 5.2 Other formats........................ 5.3 Example: Wide-form snapshot data............ Using stset 6.1 A short lesson on dates................... 6.2 Purposes of the stset command.............. 6.3 Syntax of the stset command............... 6.3.1 Specifying analysis time............. 6.3.2 Variables defined by stset ............ 6.3.3 Specifying what constitutes failure....... 6.3.4 Specifying when subjects exit from the analysis 6.3.5 Specifying when subjects enter the analysis . . 6.3.6 Specifying the subject-ID variable........ 6.3.7 Specifying the begin-of-span variable...... 6.3.8 Convenience options............... After stset 7.1 Look at stset’s output.................. 7.2 List some of your data.................. 7.3 Use stdescribe....................... 7.4 Use stvary ....................
Contents vii 7.5 Perhaps use stfill............................. 81 7.6 Example: Hip-fracture data....................... 83 8 Nonparamet rie analysis 91 8.1 Inadequacies of standard univariate methods ............. 91 8.2 The Kaplan-Meier estimator ...................... 93 8.2.1 Calculation ........................... 93 8.2.2 Censoring............................ 96 8.2.3 Left-truncation (delayed entry) ................ 97 8.2.4 Gaps............................... 99 8.2.5 Relationship to the empirical distribution function..... 99 8.2.6 Other uses of sts list...................... 101 8.2.7 Graphing the Kaplan-Meier estimate............. 102 8.3 The Nelson-Aalen estimator....................... 107 8.4 Estimating the hazard function..................... 113 8.5 Estimating mean and median survival times.............. 118 8.6 Tests of hypothesis............................ 122 8.6.1 The log-rank test........................ 123 8.6.2 The Wilcoxon test ....................... 125 8.6.3 Other tests ........................... 126 8.6.4 Stratified tests.......................... 126 9 The Cox proportional hazards model 131 9.1 Using stcox................................ 132 9.1.1 The Cox model has no intercept................ 133 9.1.2 Interpreting coefficients..................... 133 9.1.3 The effect of units on coefficients............... 135 9.1.4 Estimating the baseline cumulative hazard and survivor functions............................. 137 9.1.5 Estimating the baseline hazard function........... 141 9.1.6 The effect of units on the baseline functions......... 145 9.2 Likelihood calculations.......................... 147
Contents viii 9.2.1 No tied failures......................... 147 9.2.2 Tied failures........................... 15 0 The marginal calculation.................... 150 The partial calculation..................... 151 The Breslow approximation.................. 152 The Efron approximation ................... 153 9.2.3 Summary ............................ 153 9.3 Stratified analysis............................. 155 9.3.1 Obtaining coefficient estimates ................ 155 9.3.2 Obtaining estimates of baseline functions........... 157 9.4 Cox models with shared frailty..................... 158 9.4.1 Parameter estimation...................... 160 9.4.2 Obtaining estimates of baseline functions........... 164 9.5 Cox models with survey data...................... 167 9.5.1 Declaring survey characteristics................ 168 9.5.2 Fitting a Cox model with survey data ............ 169 9.5.3 Some caveats of analyzing survival data from complex survey designs.......................... 171 9.6 Cox model with missing data—multiple imputation.......... 172 9.6.1 Imputing missing values.................... 174 9.6.2 Multiple-imputation inference................. 176 10 Model building using stcox 179 10.1 Indicator variables............................ 179 10.2 Categorical variables........................... 180 10.3 Continuous variables........................... 182 10.3.1 Fractional polynomials..................... 184 10.4 Interactions................................ 188 10.5 Time-varying variables.......................... 191 10.5.1 Using stcox, tvc() texp().................... 193 10.5.2 Using stsplit . 195
Contents IX 10.6 Modeling group effects: fixed-effects, random-effects, stratification, and clustering............................ 199 11 The Cox model: Diagnostics 205 11.1 Testing the proportional-hazards assumption ............. 205 11.1.1 Tests based on reestimation.................. 205 11.1.2 Test based on Schoenfeld residuals .............. 209 11.1.3 Graphical methods....................... 211 11.2 Residuals and diagnostic measures................... 214 Reye’s syndrome data ..................... 215 11.2.1 Determining functional form.................. 216 11.2.2 Goodness of fit ......................... 221 11.2.3 Outliers and influential points................. 225 12 Parametric models 231 12.1 Motivation................................. 231 12.2 Classes of parametric models ...................... 234 12.2.1 Parametric proportional hazards models........... 236 12.2.2 Accelerated failure-time models................ 241 12.2.3 Comparing the two parameterizations ............ 243 13 A survey of basic parametric regression models in Stata 247 13.1 The exponential model.......................... 249 13.1.1 Exponential regression in the PH metric........... 249 13.1.2 Exponential regression in the AFT metric.......... 256 13.2 Weibull regression ............................ 259 13.2.1 Weibull regression in the PH metric.............. 259 Fitting null models....................... 263 13.2.2 Weibull regression in the AFT metric............. 267 13.3 Gompertz regression (PH metric).................... 268 13.4 Lognormal regression (AFT metric)................... 271 13.5 Loglogistic regression (AFT metric)................... 275 13.6 Generalized gamma regression (AFT metric) ............. 278
280 280 283 285 285 287 293 296 298 302 302 302 307 309 311 317 317 323 326 327 328 333 341 349 352 352 354 358 362 365 13.7 Choosing among parametric models............... 13.7.1 Nested models...................... 13.7.2 Nonnested models.................... Postestimation commands for parametric models 14.1 Use of predict after streg..................... 14.1.1 Predicting the time of failure ............. 14.1.2 Predicting the hazard and related functions..... 14.1.3 Calculating residuals.................. 14.2 Using stcurve........................... 14.3 Predictive margins and marginal effects ............ 14.3.1 Predictive margins................... Marginal mean survival time.............. Marginal survival probabilities............ Multiple-record data.................. 14.3.2 Marginal effects..................... Generalizing the parametric regression model 15.0. 3 Using the ancillary() option.............. 15.0. 4 Stratified models.................... 15.1 Frailty models........................... 15.1.1 Unshared-frailty models................ 15.1.2 Example: Kidney data................. 15.1.3 Testing for heterogeneity................ 15.1.4 Shared-frailty models.................. Power and sample-size determination for survival analysis 16.1 Estimating sample size...................... 16.1.1 Multiple-myeloma data................. 16.1.2 Comparing two survivor functions nonparametrically 16.1.3 Comparing two exponential survivor functions . . . . 16.1.4 Cox regression models................. 16.2 Accounting for withdrawal and accrual of subjects......
Contents xi 16.2.1 The effect of withdrawal or loss to follow-up......... 365 16.2.2 The effect of accrual...................... 366 16.2.3 Examples ............................ 369 16.3 Estimating power and effect size .................... 376 16.4 Tabulating or graphing results...... 377 17 Competing risks 381 17.1 Cause-specific hazards.......................... 382 17.2 Cumulative incidence functions..................... 383 17.3 Nonparametric analysis ......................... 384 17.3.1 Breast cancer data....................... 385 17.3.2 Cause-specific hazards..................... 386 17.3.3 Cumulative incidence functions................ 389 17.4 Semiparametric analysis......................... 392 17.4.1 Cause-specific hazards..................... 392 Simultaneous regressions for cause-specific hazards.....395 17.4.2 Cumulative incidence functions................ 399 Using stcrreg .......................... 399 Using stcox........................... 406 17.5 Parametric analysis............................ 407 References 409 Author index 417 Subject index 421
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| any_adam_object | 1 |
| author | Cleves, Mario Alberto 1954- Gould, William 1952- Marchenko, Yulia V. |
| author_GND | (DE-588)136053076 (DE-588)1059407698 (DE-588)1114150320 |
| author_facet | Cleves, Mario Alberto 1954- Gould, William 1952- Marchenko, Yulia V. |
| author_role | aut aut aut |
| author_sort | Cleves, Mario Alberto 1954- |
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| ctrlnum | (OCoLC)951447376 (DE-599)BVBBV043582419 |
| discipline | Informatik Soziologie Psychologie Mathematik Wirtschaftswissenschaften |
| edition | Revised third edition |
| format | Book |
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| spelling | Cleves, Mario Alberto 1954- Verfasser (DE-588)136053076 aut An introduction to survival analysis using Stata Mario A. Cleves (Department of Pediatrics, University of Arkansas Medical Sciences), William Gould (StataCorp), Yulia V. Marchenko (StataCrop) Revised third edition College Station, Texas Stata Press [2016] xxx, 428 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier A Stata Press publication Ereignisdatenanalyse (DE-588)4132103-0 gnd rswk-swf Statistische Analyse (DE-588)4116599-8 gnd rswk-swf Überleben (DE-588)4117273-5 gnd rswk-swf Stata (DE-588)4617285-3 gnd rswk-swf Ereignisdatenanalyse (DE-588)4132103-0 s Statistische Analyse (DE-588)4116599-8 s Stata (DE-588)4617285-3 s DE-604 Überleben (DE-588)4117273-5 s 1\p DE-604 Gould, William 1952- Verfasser (DE-588)1059407698 aut Marchenko, Yulia V. Verfasser (DE-588)1114150320 aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028997043&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Cleves, Mario Alberto 1954- Gould, William 1952- Marchenko, Yulia V. An introduction to survival analysis using Stata Ereignisdatenanalyse (DE-588)4132103-0 gnd Statistische Analyse (DE-588)4116599-8 gnd Überleben (DE-588)4117273-5 gnd Stata (DE-588)4617285-3 gnd |
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| title | An introduction to survival analysis using Stata |
| title_auth | An introduction to survival analysis using Stata |
| title_exact_search | An introduction to survival analysis using Stata |
| title_full | An introduction to survival analysis using Stata Mario A. Cleves (Department of Pediatrics, University of Arkansas Medical Sciences), William Gould (StataCorp), Yulia V. Marchenko (StataCrop) |
| title_fullStr | An introduction to survival analysis using Stata Mario A. Cleves (Department of Pediatrics, University of Arkansas Medical Sciences), William Gould (StataCorp), Yulia V. Marchenko (StataCrop) |
| title_full_unstemmed | An introduction to survival analysis using Stata Mario A. Cleves (Department of Pediatrics, University of Arkansas Medical Sciences), William Gould (StataCorp), Yulia V. Marchenko (StataCrop) |
| title_short | An introduction to survival analysis using Stata |
| title_sort | an introduction to survival analysis using stata |
| topic | Ereignisdatenanalyse (DE-588)4132103-0 gnd Statistische Analyse (DE-588)4116599-8 gnd Überleben (DE-588)4117273-5 gnd Stata (DE-588)4617285-3 gnd |
| topic_facet | Ereignisdatenanalyse Statistische Analyse Überleben Stata |
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