Modelling generalized linear (loglinear) models for raters agreement measure: with complete and missing values cases
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis Book |
| Language: | English |
| Published: |
Frankfurt am Main
Lang
2005
|
| Series: | Anwendungsorientierte Statistik
9 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Zusammenfassung dt. und engl. |
| Physical Description: | 246 S. graph. Darst. |
| ISBN: | 3631543689 0820477826 |
Staff View
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| 245 | 1 | 0 | |a Modelling generalized linear (loglinear) models for raters agreement measure |b with complete and missing values cases |c Adebowale Olusola Adejumo |
| 264 | 1 | |a Frankfurt am Main |b Lang |c 2005 | |
| 300 | |a 246 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 490 | 1 | |a Anwendungsorientierte Statistik |v 9 | |
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| 502 | |a Zugl.: München, Univ., Diss., 2005 | ||
| 650 | 4 | |a Expectation-maximization algorithms | |
| 650 | 4 | |a Log-linear models | |
| 650 | 4 | |a Missing observations (Statistics) | |
| 650 | 4 | |a Negative binomial distribution | |
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Record in the Search Index
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|---|---|
| adam_text | Contents
1 General introduction 5
1.1 Why modelling in Raters Agreement measures? 5
1.2 Scales of measurements 8
1.3 Description of Data for Raters agreement 10
1.4 Association and agreement Measures 17
1.5 Scope of the study 17
2 Contingency tables 18
2.1 Introduction 18
2.2 Tabulation 18
2.2.1 One dimensional (1 x J contingency) tables 19
2.2.2 Two dimensional (I x J contingency) tables 19
2.2.3 Square tables (I x I contingency) tables 21
2.2.4 Multidimensional tables 22
2.3 Common sampling distributions for two way classifications 23
2.3.1 Poisson sampling 23
2.3.2 Multinomial sampling 23
2.3.3 Product Multinomial sampling 24
2.3.4 Special sampling plans 24
2.4 Likelihood Functions and Maximum Likelihood estimates 25
2.5 Testing Goodness of fit 27
2.5.1 Pearson chi squared statistic 27
2 CONTENTS
2.5.2 Likelihood Ratio statistic 28
3 Generalized Linear and Loglinear Models 30
3.1 Introduction: 30
3.2 Generalized Linear Models (GLMs) 31
3.2.1 The components of Generalized Linear Models: 33
3.2.2 Common distributions in the Exponential family used with
GLMs: 34
3.2.3 Maximum likelihood estimation for GLMs 38
3.2.4 Analysis of Deviance 44
3.3 Loglinear models 45
3.3.1 Sampling scheme for loglinear models 46
3.3.2 Maximum likelihood estimation 55
3.3.3 Assessing the goodness of fit of loglinear models 63
4 Association and Agreement Measures 67
4.1 Introduction 67
4.2 Measures of association 68
4.2.1 Basic measures of association 69
4.3 Measures of Agreement 76
4.3.1 Basic measures of Agreement 78
4.3.2 Modelling in Agreement measure 91
5 Modelling and fitting of selected models 97
5.1 Introduction 97
5.2 Modelling baseline structures 98
5.3 Some selected models 99
5.3.1 Symmetry models (SM) 99
5.3.2 Conditional symmetry models (CS) 100
5.3.3 Quasi symmetry model (QS) 103
5.3.4 Uniform association model (UA) 105
5.3.5 Homogeneous agreement model (HA) 107
CONTENTS 3
5.3.6 Uniform association model plus extra agreement (UAA). . . . 108
5.3.7 Mover Stayer model (MS) 109
5.3.8 Bradley Terry model (BT) Ill
5.4 Fitting of the selected models 113
5.5 Simulation work and results 119
5.5.1 Simulation work 119
5.5.2 Results 121
6 Modelling Quasi independence and association for agreement 131
6.1 Introduction 131
6.2 Quasi independence Model (QID) 132
6.3 Quasi association (QA) 135
6.4 Fitting of the models 142
6.5 Simulation work and results 144
7 Modelling Negative binomial for agreement 157
7.1 Introduction 157
7.2 Why negative binomial model for agreement? 157
7.3 Model and its properties 159
7.4 Modelling and estimation of parameters 161
7.5 Applications to real life data and Results 168
7.5.1 Applications to real life data 168
7.5.2 Results 169
8 Missing ratings:Likelihood and Data based approaches 182
8.1 Introduction on missing values in general 182
8.1.1 Missing values pattern in general 184
8.1.2 Missing values mechanisms in general 186
8.2 Missing values in categorical data 187
8.2.1 Missing values in the ratings of raters 192
8.2.2 Missing ratings pattern 194
8.2.3 Missing ratings mechanisms 197
4 CONTENTS
8.3 Maximum likelihood estimation in incomplete ratings case 198
8.3.1 Expectation Maximization (EM) 202
8.4 Data based approach in incomplete ratings case 204
8.4.1 Case by case formulations for missing structures with (PMAPS) 207
8.5 Simulation study and results 208
8.5.1 Simulation study 208
8.5.2 Results 214
9 Summary and Conclusion 219
9.1 Introduction 219
9.2 Summary 219
9.3 Conclusion 222
References 224
A Appendix for Chapter 4 239
A.I Exponential logarithm notation {exp —log} 239
A.1.1 Gamma statistic 240
A.1.2 Somer s d statistic 240
A.1.3 Kendall s tau b 240
A. 1.4 Pearson s correlation coefficient 241
A.1.5 Cohen s kappa 242
A.1.6 Response function F for various kappa indices 244
|
| adam_txt |
Contents
1 General introduction 5
1.1 Why modelling in Raters Agreement measures? 5
1.2 Scales of measurements 8
1.3 Description of Data for Raters agreement 10
1.4 Association and agreement Measures 17
1.5 Scope of the study 17
2 Contingency tables 18
2.1 Introduction 18
2.2 Tabulation 18
2.2.1 One dimensional (1 x J contingency) tables 19
2.2.2 Two dimensional (I x J contingency) tables 19
2.2.3 Square tables (I x I contingency) tables 21
2.2.4 Multidimensional tables 22
2.3 Common sampling distributions for two way classifications 23
2.3.1 Poisson sampling 23
2.3.2 Multinomial sampling 23
2.3.3 Product Multinomial sampling 24
2.3.4 Special sampling plans 24
2.4 Likelihood Functions and Maximum Likelihood estimates 25
2.5 Testing Goodness of fit 27
2.5.1 Pearson chi squared statistic 27
2 CONTENTS
2.5.2 Likelihood Ratio statistic 28
3 Generalized Linear and Loglinear Models 30
3.1 Introduction: 30
3.2 Generalized Linear Models (GLMs) 31
3.2.1 The components of Generalized Linear Models: 33
3.2.2 Common distributions in the Exponential family used with
GLMs: 34
3.2.3 Maximum likelihood estimation for GLMs 38
3.2.4 Analysis of Deviance 44
3.3 Loglinear models 45
3.3.1 Sampling scheme for loglinear models 46
3.3.2 Maximum likelihood estimation 55
3.3.3 Assessing the goodness of fit of loglinear models 63
4 Association and Agreement Measures 67
4.1 Introduction 67
4.2 Measures of association 68
4.2.1 Basic measures of association 69
4.3 Measures of Agreement 76
4.3.1 Basic measures of Agreement 78
4.3.2 Modelling in Agreement measure 91
5 Modelling and fitting of selected models 97
5.1 Introduction 97
5.2 Modelling baseline structures 98
5.3 Some selected models 99
5.3.1 Symmetry models (SM) 99
5.3.2 Conditional symmetry models (CS) 100
5.3.3 Quasi symmetry model (QS) 103
5.3.4 Uniform association model (UA) 105
5.3.5 Homogeneous agreement model (HA) 107
CONTENTS 3
5.3.6 Uniform association model plus extra agreement (UAA). . . . 108
5.3.7 Mover Stayer model (MS) 109
5.3.8 Bradley Terry model (BT) Ill
5.4 Fitting of the selected models 113
5.5 Simulation work and results 119
5.5.1 Simulation work 119
5.5.2 Results 121
6 Modelling Quasi independence and association for agreement 131
6.1 Introduction 131
6.2 Quasi independence Model (QID) 132
6.3 Quasi association (QA) 135
6.4 Fitting of the models 142
6.5 Simulation work and results 144
7 Modelling Negative binomial for agreement 157
7.1 Introduction 157
7.2 Why negative binomial model for agreement? 157
7.3 Model and its properties 159
7.4 Modelling and estimation of parameters 161
7.5 Applications to real life data and Results 168
7.5.1 Applications to real life data 168
7.5.2 Results 169
8 Missing ratings:Likelihood and Data based approaches 182
8.1 Introduction on missing values in general 182
8.1.1 Missing values pattern in general 184
8.1.2 Missing values mechanisms in general 186
8.2 Missing values in categorical data 187
8.2.1 Missing values in the ratings of raters 192
8.2.2 Missing ratings pattern 194
8.2.3 Missing ratings mechanisms 197
4 CONTENTS
8.3 Maximum likelihood estimation in incomplete ratings case 198
8.3.1 Expectation Maximization (EM) 202
8.4 Data based approach in incomplete ratings case 204
8.4.1 Case by case formulations for missing structures with (PMAPS) 207
8.5 Simulation study and results 208
8.5.1 Simulation study 208
8.5.2 Results 214
9 Summary and Conclusion 219
9.1 Introduction 219
9.2 Summary 219
9.3 Conclusion 222
References 224
A Appendix for Chapter 4 239
A.I Exponential logarithm notation {exp —log} 239
A.1.1 Gamma statistic 240
A.1.2 Somer's d statistic 240
A.1.3 Kendall's tau b 240
A. 1.4 Pearson's correlation coefficient 241
A.1.5 Cohen's kappa 242
A.1.6 Response function F for various kappa indices 244 |
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| callnumber-subject | QA - Mathematics |
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| dewey-ones | 519 - Probabilities and applied mathematics |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Mathematik Wirtschaftswissenschaften |
| format | Thesis Book |
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| index_date | 2024-07-02T13:42:48Z |
| indexdate | 2024-07-09T20:34:11Z |
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| language | English |
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| series | Anwendungsorientierte Statistik |
| series2 | Anwendungsorientierte Statistik |
| spelling | Adejumo, Adebowale Olusola Verfasser aut Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases Adebowale Olusola Adejumo Frankfurt am Main Lang 2005 246 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Anwendungsorientierte Statistik 9 Zusammenfassung dt. und engl. Zugl.: München, Univ., Diss., 2005 Expectation-maximization algorithms Log-linear models Missing observations (Statistics) Negative binomial distribution Kontingenztafel (DE-588)4165159-5 gnd rswk-swf Log-lineares Modell (DE-588)4036197-4 gnd rswk-swf Kappa-Koeffizient (DE-588)7522376-4 gnd rswk-swf Urteilerübereinstimmung (DE-588)7522360-0 gnd rswk-swf Negative Binomialverteilung (DE-588)4194810-5 gnd rswk-swf Fehlende Daten (DE-588)4264715-0 gnd rswk-swf Verallgemeinertes lineares Modell (DE-588)4124382-1 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Urteilerübereinstimmung (DE-588)7522360-0 s Fehlende Daten (DE-588)4264715-0 s DE-604 Kappa-Koeffizient (DE-588)7522376-4 s Kontingenztafel (DE-588)4165159-5 s Log-lineares Modell (DE-588)4036197-4 s Verallgemeinertes lineares Modell (DE-588)4124382-1 s Negative Binomialverteilung (DE-588)4194810-5 s Anwendungsorientierte Statistik 9 (DE-604)BV011148252 9 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014585466&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Adejumo, Adebowale Olusola Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases Anwendungsorientierte Statistik Expectation-maximization algorithms Log-linear models Missing observations (Statistics) Negative binomial distribution Kontingenztafel (DE-588)4165159-5 gnd Log-lineares Modell (DE-588)4036197-4 gnd Kappa-Koeffizient (DE-588)7522376-4 gnd Urteilerübereinstimmung (DE-588)7522360-0 gnd Negative Binomialverteilung (DE-588)4194810-5 gnd Fehlende Daten (DE-588)4264715-0 gnd Verallgemeinertes lineares Modell (DE-588)4124382-1 gnd |
| subject_GND | (DE-588)4165159-5 (DE-588)4036197-4 (DE-588)7522376-4 (DE-588)7522360-0 (DE-588)4194810-5 (DE-588)4264715-0 (DE-588)4124382-1 (DE-588)4113937-9 |
| title | Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases |
| title_auth | Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases |
| title_exact_search | Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases |
| title_exact_search_txtP | Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases |
| title_full | Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases Adebowale Olusola Adejumo |
| title_fullStr | Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases Adebowale Olusola Adejumo |
| title_full_unstemmed | Modelling generalized linear (loglinear) models for raters agreement measure with complete and missing values cases Adebowale Olusola Adejumo |
| title_short | Modelling generalized linear (loglinear) models for raters agreement measure |
| title_sort | modelling generalized linear loglinear models for raters agreement measure with complete and missing values cases |
| title_sub | with complete and missing values cases |
| topic | Expectation-maximization algorithms Log-linear models Missing observations (Statistics) Negative binomial distribution Kontingenztafel (DE-588)4165159-5 gnd Log-lineares Modell (DE-588)4036197-4 gnd Kappa-Koeffizient (DE-588)7522376-4 gnd Urteilerübereinstimmung (DE-588)7522360-0 gnd Negative Binomialverteilung (DE-588)4194810-5 gnd Fehlende Daten (DE-588)4264715-0 gnd Verallgemeinertes lineares Modell (DE-588)4124382-1 gnd |
| topic_facet | Expectation-maximization algorithms Log-linear models Missing observations (Statistics) Negative binomial distribution Kontingenztafel Log-lineares Modell Kappa-Koeffizient Urteilerübereinstimmung Negative Binomialverteilung Fehlende Daten Verallgemeinertes lineares Modell Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014585466&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV011148252 |
| work_keys_str_mv | AT adejumoadebowaleolusola modellinggeneralizedlinearloglinearmodelsforratersagreementmeasurewithcompleteandmissingvaluescases |