Applied logistic regression:
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Hoboken, NJ
Wiley
2013
|
| Ausgabe: | 3. ed. |
| Schriftenreihe: | Wiley series in probability and statistics
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025470317&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XVI, 500 S. graph. Darst. |
| ISBN: | 9780470582473 |
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Datensatz im Suchindex
| DE-BY-TUM_call_number | 0102 MAT 628f 2001 A 18544(3) |
|---|---|
| DE-BY-TUM_katkey | 1906573 |
| DE-BY-TUM_location | 01 |
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| _version_ | 1821933968332685312 |
| adam_text | Titel: Applied logistic regression
Autor: Hosmer, David W
Jahr: 2013
Contents
Preface to the Third Edition
1 Introduction to the Logistic Regression Model
1.1 Introduction, 1
1.2 Fitting the Logistic Regression Model, 8
1.3 Testing for the Significance of the Coefficients, 10
1.4 Confidence Interval Estimation, 15
1.5 Other Estimation Methods, 20
1.6 Data Sets Used in Examples and Exercises, 22
1.6.1 The ICU Study, 22
1.6.2 The Low Birth Weight Study, 24
1.6.3 The Global Longitudinal Study of Osteoporosis
in Women, 24
1.6.4 The Adolescent Placement Study, 26
1.6.5 The Burn Injury Study, 27
1.6.6 The Myopia Study, 29
1.6.7 The NHANES Study, 31
1.6.8 The Polypharmacy Study, 31
Exercises, 32
2 The Multiple Logistic Regression Model
2.1 Introduction, 35
2.2 The Multiple Logistic Regression Model, 35
2.3 Fitting the Multiple Logistic Regression Model, 37
2.4 Testing for the Significance of the Model, 39
2.5 Confidence Interval Estimation, 42
2.6 Other Estimation Methods, 45
Exercises, 46
viii
CONTENTS
3 Interpretation of the Fitted Logistic Regression Model 49
3.1 Introduction, 49
3.2 Dichotomous Independent Variable, 50
3.3 Polychotomous Independent Variable, 56
3.4 Continuous Independent Variable, 62
3.5 Multivariable Models, 64
3.6 Presentation and Interpretation of the Fitted Values, 77
3.7 A Comparison of Logistic Regression and Stratified Analysis
for 2 X 2 Tables, 82
Exercises, 87
4 Model-Building Strategies and Methods for Logistic Regression 89
4.1 Introduction, 89
4.2 Purposeful Selection of Covariates, 89
4.2.1 Methods to Examine the Scale of a Continuous
Covariate in the Logit, 94
4.2.2 Examples of Purposeful Selection, 107
4.3 Other Methods for Selecting Covariates, 124
4.3.1 Stepwise Selection of Covariates, 125
4.3.2 Best Subsets Logistic Regression, 133
4.3.3 Selecting Covariates and Checking their Scale
Using Multivariable Fractional Polynomials, 139
4.4 Numerical Problems, 145
Exercises, 150
5 Assessing the Fit of the Model 153
5.1 Introduction, 153
5.2 Summary Measures of Goodness of Fit, 154
5.2.1 Pearson Chi-Square Statistic, Deviance,
and Sum-of-Squares, 155
5.2.2 The Hosmer-Lemeshow Tests, 157
5.2.3 Classification Tables, 169
5.2.4 Area Under the Receiver Operating Characteristic
Curve, 173
5.2.5 Other Summary Measures, 182
5.3 Logistic Regression Diagnostics, 186
5.4 Assessment of Fit via External Validation, 202
CONTENTS
5.5 Interpretation and Presentation of the Results from a Fitted
Logistic Regression Model, 212
Exercises, 223
6 Application of Logistic Regression with Different Sampling
Models
6.1 Introduction, 227
6.2 Cohort Studies, 227
6.3 Case-Control Studies, 229
6.4 Fitting Logistic Regression Models to Data from Complex
Sample Surveys, 233
Exercises, 242
7 Logistic Regression for Matched Case-Control Studies
7.1 Introduction, 243
7.2 Methods For Assessment of Fit in a I -M Matched
Study, 248
7.3 An Example Using the Logistic Regression Model in a 1-1
Matched Study, 251
7.4 An Example Using the Logistic Regression Model in a 1 -M
Matched Study, 260
Exercises, 267
8 Logistic Regression Models for Multinomial and Ordinal
Outcomes
8.1 The Multinomial Logistic Regression Model, 269
8.1.1 Introduction to the Model and Estimation of Model
Parameters, 269
8.1.2 Interpreting and Assessing the Significance of the
Estimated Coefficients, 272
8.1.3 Model-Building Strategies for Multinomial Logistic
Regression, 278
8.1.4 Assessment of Fit and Diagnostic Statistics for the
Multinomial Logistic Regression Model, 283
8.2 Ordinal Logistic Regression Models, 289
8.2.1 Introduction to the Models, Methods for Fitting, and
Interpretation of Model Parameters, 289
8.2.2 Model Building Strategies for Ordinal Logistic
Regression Models, 305
Exercises, 310
CONTENTS
9 Logistic Regression Models for the Analysis of Correlated Data 313
9.1 Introduction, 313
9.2 Logistic Regression Models for the Analysis of Correlated
Data, 315
9.3 Estimation Methods for Correlated Data Logistic Regression
Models, 318
9.4 Interpretation of Coefficients from Logistic Regression
Models for the Analysis of Correlated Data, 323
9.4.1 Population Average Model, 324
9.4.2 Cluster-Specific Model, 326
9.4.3 Alternative Estimation Methods for the
Cluster-Specific Model, 333
9.4.4 Comparison of Population Average and
Cluster-Specific Model, 334
9.5 An Example of Logistic Regression Modeling with
Correlated Data, 337
9.5.1 Choice of Model for Correlated Data Analysis, 338
9.5.2 Population Average Model, 339
9.5.3 Cluster-Specific Model, 344
9.5.4 Additional Points to Consider when Fitting Logistic
Regression Models to Correlated Data, 351
9.6 Assessment of Model Fit, 354
9.6.1 Assessment of Population Average Model Fit, 354
9.6.2 Assessment of Cluster-Specific Model Fit, 365
9.6.3 Conclusions, 374
Exercises, 375
10 Special Topics 377
10.1 Introduction, 377
10.2 Application of Propensity Score Methods in Logistic
Regression Modeling, 377
10.3 Exact Methods for Logistic Regression Models, 387
10.4 Missing Data, 395
10.5 Sample Size Issues when Fitting Logistic Regression
Models, 401
10.6 Bayesian Methods for Logistic Regression, 408
10.6.1 The Bayesian Logistic Regression Model, 410
10.6.2 MCMC Simulation, 411
CONTENTS
xi
10.6.3 An Example of a Bayesian Analysis and Its
Interpretation, 419
10.7 Other Link Functions for Binary Regression Models, 434
10.8 Mediation, 441
10.8.1 Distinguishing Mediators from Confounders, 441
10.8.2 Implications for the Interpretation of an Adjusted
Logistic Regression Coefficient, 443
10.8.3 Why Adjust for a Mediator? 444
10.8.4 Using Logistic Regression to Assess Mediation:
Assumptions, 445
10.9 More About Statistical Interaction, 448
10.9.1 Additive versus Multiplicative Scale-Risk
Difference versus Odds Ratios, 448
10.9.2 Estimating and Testing Additive Interaction, 451
Exercises, 456
References 459
Index
479
|
| any_adam_object | 1 |
| author | Hosmer, David W. 1944- Lemeshow, Stanley 1948- Sturdivant, Rodney X. |
| author_GND | (DE-588)172144329 (DE-588)136273823 (DE-588)1034375938 |
| author_facet | Hosmer, David W. 1944- Lemeshow, Stanley 1948- Sturdivant, Rodney X. |
| author_role | aut aut aut |
| author_sort | Hosmer, David W. 1944- |
| author_variant | d w h dw dwh s l sl r x s rx rxs |
| building | Verbundindex |
| bvnumber | BV040643283 |
| classification_rvk | MR 2100 QH 252 SK 840 |
| classification_tum | MAT 628f |
| ctrlnum | (OCoLC)844024791 (DE-599)BVBBV040643283 |
| discipline | Soziologie Mathematik Wirtschaftswissenschaften |
| edition | 3. ed. |
| format | Book |
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| id | DE-604.BV040643283 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T16:19:32Z |
| institution | BVB |
| isbn | 9780470582473 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025470317 |
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| physical | XVI, 500 S. graph. Darst. |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Wiley |
| record_format | marc |
| series2 | Wiley series in probability and statistics |
| spellingShingle | Hosmer, David W. 1944- Lemeshow, Stanley 1948- Sturdivant, Rodney X. Applied logistic regression Epidemiologie (DE-588)4015016-1 gnd Regressionsmodell (DE-588)4127980-3 gnd Biostatistik (DE-588)4729990-3 gnd Anwendung (DE-588)4196864-5 gnd Regressionsanalyse (DE-588)4129903-6 gnd |
| subject_GND | (DE-588)4015016-1 (DE-588)4127980-3 (DE-588)4729990-3 (DE-588)4196864-5 (DE-588)4129903-6 |
| title | Applied logistic regression |
| title_auth | Applied logistic regression |
| title_exact_search | Applied logistic regression |
| title_full | Applied logistic regression David W. Hosmer ; Stanley Lemeshow ; Rodney X. Sturdivant |
| title_fullStr | Applied logistic regression David W. Hosmer ; Stanley Lemeshow ; Rodney X. Sturdivant |
| title_full_unstemmed | Applied logistic regression David W. Hosmer ; Stanley Lemeshow ; Rodney X. Sturdivant |
| title_short | Applied logistic regression |
| title_sort | applied logistic regression |
| topic | Epidemiologie (DE-588)4015016-1 gnd Regressionsmodell (DE-588)4127980-3 gnd Biostatistik (DE-588)4729990-3 gnd Anwendung (DE-588)4196864-5 gnd Regressionsanalyse (DE-588)4129903-6 gnd |
| topic_facet | Epidemiologie Regressionsmodell Biostatistik Anwendung Regressionsanalyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025470317&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT hosmerdavidw appliedlogisticregression AT lemeshowstanley appliedlogisticregression AT sturdivantrodneyx appliedlogisticregression |
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Teilbibliothek Mathematik & Informatik
| Signatur: |
0102 MAT 628f 2001 A 18544(3) Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |