Research methodology in the life, behavioural and social sciences:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
London [u.a.]
Sage
1999
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XVII, 393 S. graph. Darst. |
| ISBN: | 0761958835 0761958843 |
Internformat
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| 245 | 1 | 0 | |a Research methodology in the life, behavioural and social sciences |c ed. by Herman J. Adèr ... |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a London [u.a.] |b Sage |c 1999 | |
| 300 | |a XVII, 393 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 7 | |a Kwantitatieve methoden |2 gtt | |
| 650 | 4 | |a Life sciences - Methodology | |
| 650 | 4 | |a Life sciences - Research - Methodology | |
| 650 | 7 | |a Methodologie |2 gtt | |
| 650 | 4 | |a Psychologie - Recherche - Méthodologie | |
| 650 | 4 | |a Sciences - Méthodologie | |
| 650 | 4 | |a Sciences de la vie - Recherche - Méthodologie | |
| 650 | 4 | |a Sciences sociales - Recherche - Méthodologie | |
| 650 | 7 | |a Sociaal-wetenschappelijk onderzoek |2 gtt | |
| 650 | 4 | |a Social sciences - Research - Methodology | |
| 650 | 4 | |a Statistics | |
| 650 | 4 | |a Statistique | |
| 650 | 4 | |a Biowissenschaften | |
| 650 | 4 | |a Methode | |
| 650 | 4 | |a Sozialwissenschaften | |
| 650 | 4 | |a Statistik | |
| 650 | 4 | |a Research |x Methodology | |
| 650 | 4 | |a Social sciences |x Methodology | |
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Datensatz im Suchindex
| _version_ | 1804127506967560192 |
|---|---|
| adam_text | Contents
List of Contributors xiii
1 Introduction 1
/ 2 Historical remarks 6
6 3 Graphical representation 13
1 3.1 Common approaches in various fields 15
3.1.1 What requirements should an ideal graphical
representation fulfill? 23
3.2 Functional notation 24
3.2.1 Example: Design of a clinical trial 27
3.3 Representation of Time 27
3.4 Representation of Reasoning 30
3.5 Strategies and Context 31
3.5.1 Strategies 32
3.5.2 Context 34
3.6 Discussion 37
4 Meta data: well defined models of data sets 38
4.1 Introduction 38
4.2 Models 41
4.3 The data set 42
4.4 Well defined models of a central data set 44
4.4.1 Structure preserving functions 47
4.5 Interrelationships among models 50
4.6 Extending the elementary datum 56
4.6.1 Time 57
4.6.2 Operationalization 59
4.6.3 Well defined models for the process structure 61
4.7 Conclusion 64
5 Experimental Design 67
5.1 Concepts 68
5.1.1 The experimental process and experimental
design 68
5.1.2 Some basic terms 70
5.1.3 Treatment assignment and randomization 72
5.1.4 Experimental error, blocking and balance 72
5.1.5 Replication and pseudo replication 73
5.1.6 Characteristics of a good experimental design 74
5.2 Analysis 75
5.2.1 Relation between factors 75
5.2.2 Fixed and random factors 77
5.2.3 The model 78
5.2.4 Inference 79
5.3 An Overview of Study Designs 83
5.3.1 Designs with no block factors 84
5.3.2 Designs with one block factor 85
5.3.3 Designs with two or more block factors 87
5.3.4 More complex designs 88
5.3.5 Other types of designs 90
5.3.6 Amount of replication 90
5.4 Errors in inference 91
5.5 Power and amount of replication 92
5.6 Software for experimental design 93
6 Clinical Trials 96
6.1 Randomization 96
6.2 Alternative trial designs 97
6.3 Size of trials 98
6.4 Data monitoring 99
6.5 Regulatory issues 101
6.6 Intention to treat and non compliance 102
6.7 Outcome assessment 103
6.8 Statistical analysis and reporting 104
6.9 Meta analysis 106
6.10 Future needs 107
7 Cross sectional Research 110
7.1 Cross sectional surveys 110
7.1.1 About sample surveys 110
7.1.2 Some history of survey sampling 112
7.1.3 The survey process 113
7.2 Basic principles of sampling 116
7.2.1 The population 116
7.2.2 Selecting a sample 117
7.2.3 Computing an estimate 118
7.2.4 The simple random sample 119
7.2.5 The precision of estimates 120
7.2.6 Advanced sampling strategies 121
7.3 Practical problems 124
7.3.1 A taxonomy of errors 124
vii
7.4 The non response problem 126
7.4.1 Weighting 130
7.4.2 Imputation 132
7.5 Analysis of survey data 135
7.5.1 About Dirty Data 135
7.5.2 Exploratory analysis 135
7.5.3 Inductive analysis 137
7.5.4 Data mining 139
7.6 Further reading and Conclusions 141
8 Longitudinal Analysis 143
8.1 Preliminaries 144
8.1.1 Two ways of analysing change 144
8.1.2 Simple examples of analyses of change 146
8.2 A canonical model 147
8.2.1 State space model 148
8.2.2 ML estimation in the state space model 150
8.3 Optimal control 153
8.3.1 Outline of LQG control 154
8.3.2 Application to the psychotherapeutic process 155
8.4 Ergodicity 157
8.4.1 Simulation study 161
8.5 General discussion and conclusion 164
9 Measurement Models 168
9.1 Score models 169
9.1.1 Continuous score models 169
9.1.2 Discrete score models 173
9.2 Item response models 174
9.2.1 Continuous response 175
9.2.2 Dichotomous response 176
9.2.3 Ordinal polytomous response 179
9.2.4 Item response measurement model violation 181
9.3 Measurement precision 183
9.3.1 Information 183
9.3.2 Reliability 184
9.4 Sensitivity and specificity 185
9.5 Discussion 186
9.6 Further reading 187
10 Graphical Modelling 188
10.1 Conditional independence 190
10.2 Marginalizing and Conditioning 192
10.3 Graphical models in survey analysis 197
10.4 Graphical models for categorical variables 200
10.5 A graphical model for credit card applications 204
10.6 Models for continuous variables 209
10.7 A graphical model for foreign exchange rates 210
10.8 Concluding remarks 215
10.8.1 Further reading 217
10.8.2 Software 218
10.9 Summary 219
11 Structural Equation Modelling 220
11.1 Formulation of Structural equation
models 221
11.2 Estimation and Testing 229
11.3 Correction for Measurement error 232
11.4 Data requirements 235
11.5 Summary 237
12 Graphs, Causality, and Structural Equation Models 240
12.1 Introduction 240
12.1.1 Causality in search of a language 240
12.1.2 Causality and structural models 241
12.1.3 Graphs as a mathematical language:
an example 245
12.1.4 Chapter outline 247
12.2 Graphs and model testing 248
12.2.1 The testable implications of structural models 248
12.2.2 Testing the Testable 255
12.2.3 Model equivalence 256
12.3 Graphs and identifiability 262
12.3.1 Parameter identification in linear models 262
12.3.2 Identification in non parametric models 268
12.3.3 Causal Effects: the interventional
interpretation of structural equation models 270
12.3.4 Identification of Causal Effects 273
12.4 Some conceptual underpinnings 276
12.4.1 What do structural parameters really mean? 276
12.4.2 Interventional interpretation of effect
decomposition 281
12.5 Conclusion 283
13 Meta Analysis 285
13.1 Brief history and the role of
meta analysis in medicine 286
13.2 Combining estimators of effectiveness 288
13.2.1 Measures of treatment effectiveness 288
13.2.2 Continuous effect size measures 288
13.2.3 Categorical effect size measures 292
IX
13.2.4 Selecting an effect size measure for categorical
outcomes 297
13.2.5 Ordered categorical effect size measures 298
13.3 Combining effect size measures 299
13.4 Fixed effects models 300
13.5 Random effects models 304
13.5.1 DerSimonian Laird random effects models 305
13.5.2 Empirical Bayes and full Bayesian random effect
estimates 305
13.5.3 Robustness and publication bias 308
13.6 Exploring sources of heterogeneity 312
13.6.1 Exploratory data analysis: the Galbraith plot 313
13.6.2 Subgroup analysis 314
13.7 Meta regression 316
13.8 Meta analysis: promises and pit falls 321
i 14 Discussion 324
14.1 Context 325
14.1.1 Validity 325
14.1.2 Subfields 327
14.2 Topics 328
14.2.1 Graphical representation 328
14.2.2 Models 329
14.2.3 Causal explanation 330
14.3 Conclusions 332
Comments by David J. Hand 333
On models and theories by Jan B. Hoeksma 335
Methodology in practice and research thereupon by Dirk J. Kuik . 340
Comment: a unified theory? by P. Dick Bezemer 342
Comments on Causal Explanation by Judea Pearl 344
Additional comments by Herman J. Ader 346
A Rejoinder by Gideon J. Mellenbergh 349
? References 352
Index 381
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| indexdate | 2024-07-09T18:34:26Z |
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| language | English |
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| spelling | Research methodology in the life, behavioural and social sciences ed. by Herman J. Adèr ... 1. publ. London [u.a.] Sage 1999 XVII, 393 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Kwantitatieve methoden gtt Life sciences - Methodology Life sciences - Research - Methodology Methodologie gtt Psychologie - Recherche - Méthodologie Sciences - Méthodologie Sciences de la vie - Recherche - Méthodologie Sciences sociales - Recherche - Méthodologie Sociaal-wetenschappelijk onderzoek gtt Social sciences - Research - Methodology Statistics Statistique Biowissenschaften Methode Sozialwissenschaften Statistik Research Methodology Social sciences Methodology Statistik (DE-588)4056995-0 gnd rswk-swf Methodologie (DE-588)4139716-2 gnd rswk-swf Statistik (DE-588)4056995-0 s Methodologie (DE-588)4139716-2 s DE-604 Adèr, Herman J. Sonstige oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008728761&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Research methodology in the life, behavioural and social sciences Kwantitatieve methoden gtt Life sciences - Methodology Life sciences - Research - Methodology Methodologie gtt Psychologie - Recherche - Méthodologie Sciences - Méthodologie Sciences de la vie - Recherche - Méthodologie Sciences sociales - Recherche - Méthodologie Sociaal-wetenschappelijk onderzoek gtt Social sciences - Research - Methodology Statistics Statistique Biowissenschaften Methode Sozialwissenschaften Statistik Research Methodology Social sciences Methodology Statistik (DE-588)4056995-0 gnd Methodologie (DE-588)4139716-2 gnd |
| subject_GND | (DE-588)4056995-0 (DE-588)4139716-2 |
| title | Research methodology in the life, behavioural and social sciences |
| title_auth | Research methodology in the life, behavioural and social sciences |
| title_exact_search | Research methodology in the life, behavioural and social sciences |
| title_full | Research methodology in the life, behavioural and social sciences ed. by Herman J. Adèr ... |
| title_fullStr | Research methodology in the life, behavioural and social sciences ed. by Herman J. Adèr ... |
| title_full_unstemmed | Research methodology in the life, behavioural and social sciences ed. by Herman J. Adèr ... |
| title_short | Research methodology in the life, behavioural and social sciences |
| title_sort | research methodology in the life behavioural and social sciences |
| topic | Kwantitatieve methoden gtt Life sciences - Methodology Life sciences - Research - Methodology Methodologie gtt Psychologie - Recherche - Méthodologie Sciences - Méthodologie Sciences de la vie - Recherche - Méthodologie Sciences sociales - Recherche - Méthodologie Sociaal-wetenschappelijk onderzoek gtt Social sciences - Research - Methodology Statistics Statistique Biowissenschaften Methode Sozialwissenschaften Statistik Research Methodology Social sciences Methodology Statistik (DE-588)4056995-0 gnd Methodologie (DE-588)4139716-2 gnd |
| topic_facet | Kwantitatieve methoden Life sciences - Methodology Life sciences - Research - Methodology Methodologie Psychologie - Recherche - Méthodologie Sciences - Méthodologie Sciences de la vie - Recherche - Méthodologie Sciences sociales - Recherche - Méthodologie Sociaal-wetenschappelijk onderzoek Social sciences - Research - Methodology Statistics Statistique Biowissenschaften Methode Sozialwissenschaften Statistik Research Methodology Social sciences Methodology |
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