Negative binomial regression:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge [u.a.]
Cambridge Univ. Press
2007
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XII, 251 S. graph. Darst. |
| ISBN: | 9780521857727 |
Internformat
MARC
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Datensatz im Suchindex
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| adam_text | Contents
Preface page ix
Introduction 1
1 Overview of count response models 8
1.1 Varieties of count response model 8
1.2 Estimation 13
1.3 Fit considerations 15
1.4 Brief history of the negative binomial 15
1.5 Summary 17
2 Methods of estimation 19
2.1 Derivation of the IRLS algorithm 19
2.2 Newton—Raphson algorithms 28
2.3 The exponential family 33
2.4 Residuals for count response models 34
2.5 Summary 36
3 Poisson regression 39
3.1 Derivation of the Poisson model 39
3.2 Parameterization as a rate model 45
3.3 Testing overdispersion 46
3.4 Summary 48
4 Overdispersion 51
4.1 What is overdispersion? 51
4.2 Handling apparent overdispersion 52
4.3 Methods of handling real overdispersion 61
4.4 Summary 74
v
vi Contents
5 Negative binomial regression 77
5.1 Varieties of negative binomial 77
5.2 Derivation of the negative binomial 79
5.3 Negative binomial distributions 84
5.4 Algorithms 90
5.5 Summary 96
6 Negative binomial regression: modeling 99
6.1 Poisson versus negative binomial 99
6.2 Binomial versus count models 103
6.3 Examples: negative binomial regression 107
6.4 Summary 131
7 Alternative variance parameterizations 136
7.1 Geometric regression 137
7.2 NB 1: The linear constant model 143
7.3 NB H: Heterogeneous negative binomial regression 149
7.4 The NB P model 151
7.5 Generalized Poisson regression 154
7.6 Summary 158
8 Problems with zero counts 160
8.1 Zero truncated negative binomial 160
8.2 Negative binomial with endogenous stratification 164
8.3 Hurdle models 167
8.4 Zero inflated count models 173
8.5 Summary 177
9 Negative binomial with censoring, truncation, and sample
selection 179
9.1 Censored and truncated models econometric
parameterization 179
9.2 Censored poisson and NB 2 models survival
parameterization 186
9.3 Sample selection models 191
9.4 Summary 195
10 Negative binomial panel models 198
10.1 Unconditional fixed effects negative binomial model 199
10.2 Conditional fixed effects negative binomial model 203
10.3 Random effects negative binomial 208
10.4 Generalized estimating equation 215
Contents vii
10.5 Multilevel negative binomial models 226
10.6 Summary 230
Appendix A: Negative binomial log likelihood functions 233
Appendix B: Deviance functions 236
Appendix C: Stata negative binomial — ML algorithm 237
Appendix D: Negative binomial variance functions 239
Appendix E: Data sets 240
References 242
Author index 247
Subject index 249
|
| adam_txt |
Contents
Preface page ix
Introduction 1
1 Overview of count response models 8
1.1 Varieties of count response model 8
1.2 Estimation 13
1.3 Fit considerations 15
1.4 Brief history of the negative binomial 15
1.5 Summary 17
2 Methods of estimation 19
2.1 Derivation of the IRLS algorithm 19
2.2 Newton—Raphson algorithms 28
2.3 The exponential family 33
2.4 Residuals for count response models 34
2.5 Summary 36
3 Poisson regression 39
3.1 Derivation of the Poisson model 39
3.2 Parameterization as a rate model 45
3.3 Testing overdispersion 46
3.4 Summary 48
4 Overdispersion 51
4.1 What is overdispersion? 51
4.2 Handling apparent overdispersion 52
4.3 Methods of handling real overdispersion 61
4.4 Summary 74
v
vi Contents
5 Negative binomial regression 77
5.1 Varieties of negative binomial 77
5.2 Derivation of the negative binomial 79
5.3 Negative binomial distributions 84
5.4 Algorithms 90
5.5 Summary 96
6 Negative binomial regression: modeling 99
6.1 Poisson versus negative binomial 99
6.2 Binomial versus count models 103
6.3 Examples: negative binomial regression 107
6.4 Summary 131
7 Alternative variance parameterizations 136
7.1 Geometric regression 137
7.2 NB 1: The linear constant model 143
7.3 NB H: Heterogeneous negative binomial regression 149
7.4 The NB P model 151
7.5 Generalized Poisson regression 154
7.6 Summary 158
8 Problems with zero counts 160
8.1 Zero truncated negative binomial 160
8.2 Negative binomial with endogenous stratification 164
8.3 Hurdle models 167
8.4 Zero inflated count models 173
8.5 Summary 177
9 Negative binomial with censoring, truncation, and sample
selection 179
9.1 Censored and truncated models econometric
parameterization 179
9.2 Censored poisson and NB 2 models survival
parameterization 186
9.3 Sample selection models 191
9.4 Summary 195
10 Negative binomial panel models 198
10.1 Unconditional fixed effects negative binomial model 199
10.2 Conditional fixed effects negative binomial model 203
10.3 Random effects negative binomial 208
10.4 Generalized estimating equation 215
Contents vii
10.5 Multilevel negative binomial models 226
10.6 Summary 230
Appendix A: Negative binomial log likelihood functions 233
Appendix B: Deviance functions 236
Appendix C: Stata negative binomial — ML algorithm 237
Appendix D: Negative binomial variance functions 239
Appendix E: Data sets 240
References 242
Author index 247
Subject index 249 |
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| illustrated | Illustrated |
| index_date | 2024-07-02T18:16:50Z |
| indexdate | 2024-07-09T21:00:59Z |
| institution | BVB |
| isbn | 9780521857727 |
| language | English |
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| spelling | Hilbe, Joseph M. 1944-2017 Verfasser (DE-588)128751851 aut Negative binomial regression Joseph M. Hilbe 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2007 XII, 251 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Loi binomiale négative Poisson, Algèbres de Negative binomial distribution Poisson algebras Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Negative Binomialverteilung (DE-588)4194810-5 gnd rswk-swf Negative Binomialverteilung (DE-588)4194810-5 s Regressionsanalyse (DE-588)4129903-6 s b DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015792513&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Hilbe, Joseph M. 1944-2017 Negative binomial regression Loi binomiale négative Poisson, Algèbres de Negative binomial distribution Poisson algebras Regressionsanalyse (DE-588)4129903-6 gnd Negative Binomialverteilung (DE-588)4194810-5 gnd |
| subject_GND | (DE-588)4129903-6 (DE-588)4194810-5 |
| title | Negative binomial regression |
| title_auth | Negative binomial regression |
| title_exact_search | Negative binomial regression |
| title_exact_search_txtP | Negative binomial regression |
| title_full | Negative binomial regression Joseph M. Hilbe |
| title_fullStr | Negative binomial regression Joseph M. Hilbe |
| title_full_unstemmed | Negative binomial regression Joseph M. Hilbe |
| title_short | Negative binomial regression |
| title_sort | negative binomial regression |
| topic | Loi binomiale négative Poisson, Algèbres de Negative binomial distribution Poisson algebras Regressionsanalyse (DE-588)4129903-6 gnd Negative Binomialverteilung (DE-588)4194810-5 gnd |
| topic_facet | Loi binomiale négative Poisson, Algèbres de Negative binomial distribution Poisson algebras Regressionsanalyse Negative Binomialverteilung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015792513&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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