Cluster randomised trials:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton [u.a.]
CRC Press
2009
|
| Schriftenreihe: | Chapman & Hall, CRC interdisciplinary statistics series
A Chapman & Hall book |
| Schlagworte: | |
| Online-Zugang: | Table of contents only Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references (p. 303-307) and index |
| Beschreibung: | XXII, 315 S. Ill., graph. Darst., Kt. |
| ISBN: | 9781584888161 |
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| 245 | 1 | 0 | |a Cluster randomised trials |c Richard J. Hayes ; Lawrence H. Moulton |
| 264 | 1 | |a Boca Raton [u.a.] |b CRC Press |c 2009 | |
| 300 | |a XXII, 315 S. |b Ill., graph. Darst., Kt. | ||
| 336 | |b txt |2 rdacontent | ||
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| 490 | 0 | |a A Chapman & Hall book | |
| 500 | |a Includes bibliographical references (p. 303-307) and index | ||
| 650 | 4 | |a Clinical trials | |
| 650 | 4 | |a Cluster Analysis | |
| 650 | 4 | |a Cluster analysis | |
| 650 | 4 | |a Data Interpretation, Statistical | |
| 650 | 4 | |a Randomized Controlled Trials as Topic |x methods | |
| 700 | 1 | |a Moulton, Lawrence H. |e Verfasser |0 (DE-588)139228268 |4 aut | |
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Datensatz im Suchindex
| _version_ | 1804140890351992832 |
|---|---|
| adam_text | Contents
Preface xvii
Authors xix
Glossary of Notation xxi
Part A: Basic Concepts
1 Introduction 3
1.1 Randomised Trials 3
1.1.1 Randomising Clusters 4
1.1.2 Some Case Studies 6
1.1.3 Overview of Book 8
2 Variability between Clusters 11
2.1 Introduction 11
2.2 The Implications of Between-cluster Variability:
Some Examples 12
2.3 Measures of Between-cluster Variability 15
2.3.1 Introduction 15
2.3.1.1 Binary Outcomes and Proportions 15
2.3.1.2 Event Data and Person-years Rates 15
2.3.1.3 Quantitative Outcomes and Means 16
2.3.2 Coefficient of Variation, k 16
2.3.3 Intracluster Correlation Coefficient, p 17
2.3.3.1 Quantitative Outcomes 17
2.3.3.2 Binary Outcomes 18
2.3.3.3 Estimation of p 18
2.3.4 Relationship between k and p 18
2.4 The Design Effect 19
2.4.1 Binary Outcomes 19
2.4.2 Quantitative Outcomes 21
2.5 Sources of Within-cluster Correlation 22
2.5.1 Clustering of Population Characteristics 22
2.5.2 Variations in Response to Intervention 22
2.5.3 Correlation Due to Interaction between Individuals 23
3 Choosing Whether to Randomise by Cluster 25
3.1 Introduction 25
3.2 Rationale for Cluster Randomisation 25
3.2.1 Type of Intervention 25
ix
x Contents
3.2.2 Logistical Convenience and Acceptability 26
3.2.3 Contamination 27
3.3 Using Cluster Randomisation to Capture Indirect
Effects of Intervention 28
3.3.1 Introduction 28
3.3.2 Effects of an Intervention on Infectiousness 29
3.3.3 Mass Effects of Intervention 31
3.3.4 Direct, Indirect, Total and Overall Effects 33
3.4 Disadvantages and Limitations of Cluster
Randomisation 37
3.4.1 Efficiency 37
3.4.2 Selection Bias 37
3.4.3 Imbalances between Study Arms 39
3.4.4 Generalisability 40
Part B: Design Issues
4 Choice of Clusters 45
4.1 Introduction 45
4.2 Types of Cluster 45
4.2.1 Geographical Clusters 45
4.2.1.1 Communities 46
4.2.1.2 Administrative Units 47
4.2.1.3 Arbitrary Geographical Zones 48
4.2.2 Institutional Clusters 49
4.2.2.1 Schools 49
4.2.2.2 Health Units 50
4.2.2.3 Workplaces 50
4.2.3 Smaller Clusters 51
4.2.3.1 Households and Other Small Groups 52
4.2.3.2 Individuals as Clusters 52
4.3 Size of Clusters 53
4.3.1 Introduction 53
4.3.2 Statistical Considerations 53
4.3.3 Logistical Issues 54
4.3.4 Contamination 55
4.3.4.1 Contacts between Intervention and
Control Clusters 55
4.3.4.2 Contacts between Intervention Clusters and
the Wider Population 55
4.3.4.3 Contacts between Control Clusters
and the Wider Population 56
4.3.4.4 Effects of Cluster Size on Contamination 56
4.3.5 Transmission Zones of Infectious Diseases 56
Contents xi
4.4 Strategies to Reduce Contamination 58
4.4.1 Separation of Clusters 58
4.4.2 Buffer Zones 60
4.4.3 The Fried Egg Design 62
4.5 Levels of Randomisation, Intervention, Data Collection
and Inference 64
5 Matching and Stratification 65
5.1 Introduction 65
5.2 Rationale for Matching 65
5.2.1 Avoiding Imbalance between Treatment Arms 66
5.2.2 Improving Study Power and Precision 68
5.3 Disadvantages of Matching 70
5.3.1 Loss of Degrees of Freedom 70
5.3.2 Drop-out of Clusters 72
5.3.3 Limitations in Statistical Inference for Matched Trials 74
5.3.3.1 Adjustment for Covariates 74
5.3.3.2 Testing for Variation in Intervention Effect 74
5.3.3.3 Estimation of Intracluster Correlation
Coefficient and Coefficient of Variation 75
5.4 Stratification as an Alternative to Matching 75
5.5 Choice of Matching Variables 77
5.5.1 Estimating the Matching Correlation 77
5.5.2 Matching on Baseline Values of Endpoint of Interest 78
5.5.3 Matching on Surrogate Variables 79
5.5.4 Matching on Multiple Variables 79
5.5.5 Matching on Location 80
5.6 Choosing Whether to Match or Stratify 81
5.6.1 Introduction 81
5.6.2 Trials with a Small Number of Clusters 81
5.6.3 Trials with a Larger Number of Clusters 83
6 Randomisation Procedures 85
6.1 Introduction 85
6.2 Restricted Randomisation 86
6.2.1 Basic Principles 86
6.2.2 Using Restricted Randomisation to Achieve Overall
Balance 87
6.2.3 Balance Criteria 89
6.2.4 Validity of Restricted Randomisation 94
6.2.5 Restricted Randomisation with More than Two
Treatment Arms 99
6.3 Some Practical Aspects of Randomisation 99
6.3.1 Concealment of Allocation 99
6.3.2 Public Randomisation 99
xii Contents
7 Sample Size 105
7.1 Introduction 105
7.2 Sample Size for Unmatched Trials 106
7.2.1 Event Rates 107
7.2.2 Proportions 109
7.2.3 Means 110
7.2.4 Variable Sample Size per Cluster Ill
7.2.5 Sample Size Calculations Based on Intracluster
Correlation Coefficient Ill
7.3 Sample Size for Matched and Stratified Trials 113
7.3.1 Matched Trials 113
7.3.1.1 Event Rates 114
7.3.1.2 Proportions 114
7.3.1.3 Means 114
7.3.2 Stratified Trials 116
7.4 Estimating the Between-cluster Coefficient
of Variation 117
7.4.1 Unmatched Trials 117
7.4.1.1 Event Rates 118
7.4.1.2 Proportions 119
7.4.1.3 Means 120
7.4.2 Matched and Stratified Trials 120
7.4.2.1 Event Rates 120
7.4.2.2 Proportions and Means 121
7.5 Choice of Sample Size in each Cluster 121
7.6 Further Issues in Sample Size Calculation 124
7.6.1 Trials with More than Two Treatment Arms 124
7.6.2 Trials with Treatment Arms of Unequal Size 124
7.6.3 Equivalence Trials 125
7.6.4 Power and Precision 126
7.6.5 Assumptions about Intervention Effects 127
8 Alternative Study Designs 129
8.1 Introduction 129
8.2 Design Choices for Treatment Arms 129
8.2.1 Trials with Several Treatment Arms 129
8.2.2 Factorial Trials 130
8.2.2.1 Independent Effects 130
8.2.2.2 Non-independent Effects 132
8.2.3 Crossover Design 135
8.2.4 Stepped Wedge Design 136
8.3 Design Choices for Impact Evaluation 141
8.3.1 Introduction 141
8.3.2 Repeated Cross-sectional Samples 142
8.3.3 Cohort Follow-up 143
Contents xiii
Part C: Analytical Methods
9 Basic Principles of Analysis 149
9.1 Introduction 149
9.2 Experimental and Observational Units 149
9.3 Parameters of Interest 151
9.3.1 Event Rates 151
9.3.2 Proportions 153
9.3.2.1 Cluster-specific Odds Ratio 154
9.3.2.2 Population-average Odds Ratio 155
9.3.3 Means 156
9.3.4 More Complex Parameters 157
9.4 Approaches to Analysis 159
9.4.1 Cluster-level Analysis 159
9.4.2 Individual-level Analysis 159
9.5 Baseline Analysis 160
10 Analysis Based on Cluster-level Summaries 163
10.1 Introduction 163
10.2 Point Estimates of Intervention Effects 164
10.2.1 Point Estimates Based on Cluster Summaries 164
10.2.2 Point Estimates Based on Individual Values 165
10.2.3 Using the Logarithmic Transformation 167
10.2.4 Case Studies 168
10.3 Statistical Inference Based on the t Distribution 172
10.3.1 Unpaired /-test 172
10.3.2 Confidence Intervals Based on Cluster Summaries 173
10.3.2.1 Rate Difference 173
10.3.2.2 Rate Ratio 174
10.3.3 Case Studies 174
10.3.4 Using the Logarithmic Transformation 177
10.3.5 The Weighted f-test 178
10.4 Statistical Inference Based on a Quasi-likelihood Approach... 179
10.5 Adjusting for Covariates 182
10.5.1 Stage 1: Obtaining Covariate-adjusted Residuals 182
10.5.1.1 Event Rates 183
10.5.1.2 Proportions 183
10.5.1.3 Means 184
10.5.2 Stage 2: Using the Covariate-adjusted Residuals 184
10.5.2.1 Ratio Measures of Effect 184
10.5.2.2 Difference Measures of Effect 185
10.5.3 Case Study 186
10.6 Nonparametric Methods 189
10.6.1 Introduction 189
10.6.2 Rank Sum Test 189
10.6.3 Permutation Tests 190
10.7 Analysing for Effect Modification 194
xiv Contents
11 Regression Analysis Based on Individual-level Data 199
11.1 Introduction 199
11.2 Random Effects Models 200
11.2.1 Poisson and Cox Regressions with Random Effects 201
11.2.1.1 Poisson Regression with Random Effects 201
11.2.1.2 Cox Regression with Random Effects 207
11.2.2 Mixed Effects Linear Regression 208
11.2.3 Logistic Regression with Random Effects 213
11.3 Generalised Estimating Equations 219
11.3.1 GEE Models for Binary Data 219
11.3.2 GEE for Other Types of Outcome 221
11.4 Choice of Analytical Method 223
11.4.1 Small Numbers of Clusters 223
11.4.2 Larger Numbers of Clusters 224
11.5 Analysing for Effect Modification 225
11.6 More Complex Analyses 226
11.6.1 Controlling for Baseline Values 226
11.6.2 Repeated Measures during Follow-up 227
11.6.3 Repeated Episodes 229
12 Analysis of Trials with More Complex Designs 233
12.1 Introduction 233
12.2 Analysis of Pair-matched Trials 233
12.2.1 Introduction 233
12.2.2 Analysis Based on Cluster-level Summaries 234
12.2.3 Adjusting for Covariates 237
12.2.4 Regression Analysis Based on Individual-level
Data 241
12.3 Analysis of Stratified Trials 242
12.3.1 Introduction 242
12.3.2 Analysis Based on Cluster-level Summaries 243
12.3.3 Regression Analysis Based on Individual-level
Data 250
12.4 Analysis of Other Study Designs 251
12.4.1 Trials with More than Two Treatment Arms 251
12.4.2 Factorial Trials 252
12.4.3 Stepped Wedge Trials 253
Part D: Miscellaneous Topics
13 Ethical Considerations 257
13.1 Introduction 257
13.2 General Principles 257
13.2.1 Beneficence 258
Contents xv
13.2.2 Equity 258
13.2.3 Autonomy 259
13.3 Ethical Issues in Group Allocation 259
13.4 Informed Consent in Cluster Randomised Trials 260
13.4.1 Consent for Randomisation 261
13.4.1.1 Political Authorities 262
13.4.1.2 Village Heads 262
13.4.1.3 Community Representatives 263
13.4.1.4 Medical Practitioners 263
13.4.2 Consent for Participation 264
13.5 Other Ethical Issues 266
13.5.1 Scientific Validity 266
13.5.2 Phased Intervention Designs 266
13.5.3 Trial Monitoring 267
13.6 Conclusion 267
14 Data Monitoring 269
14.1 Introduction 269
14.2 Data Monitoring Committees 270
14.2.1 Review of DMC Responsibilities 270
14.2.2 When Are DMCs Necessary for CRTs? 271
14.2.2.1 Likelihood of Adverse Events 271
14.2.2.2 Seriousness or Severity of Outcome
Measures 271
14.2.2.3 Timing of Data Collection 272
14.2.3 Monitoring for Adverse Events 273
14.2.4 Monitoring for Efficacy 274
14.2.5 Monitoring Adequacy of Sample Size 274
14.2.6 Assessing Comparability of Treatment Arms 275
14.2.7 Approving the Analytical Plan 275
14.2.8 Presentation of Data to the DMC 276
14.3 Interim Analyses 277
14.3.1 Introduction 277
14.3.2 Timing of Interim Analyses 277
14.3.3 Stopping Rules 278
14.3.3.1 Event Rates 280
14.3.3.2 Proportions 280
14.3.3.3 Means 280
14.3.4 Disadvantages of Premature Stopping 282
15 Reporting and Interpretation 285
15.1 Introduction 285
15.2 Reporting of Cluster Randomised Trials 285
15.2.1 Overview 285
15.2.1.1 Extended CONSORT Statement 286
15.2.1.2 Publication Bias 286
xvi Contents
15.2.2 Reporting of Methods 289
15.2.2.1 Rationale for Cluster Randomisation 289
15.2.2.2 Description of Clusters and Interventions.... 289
15.2.2.3 Sample Size 290
15.2.2.4 Matching, Stratification and
Randomisation 291
15.2.2.5 Blinding and Allocation Concealment 291
15.2.2.6 Definition of Primary Endpoints 292
15.2.2.7 Statistical Methods 293
15.2.3 Reporting of Results 294
15.2.3.1 Flow Diagram 294
15.2.3.2 Baseline Comparisons 294
15.2.3.3 Analysis of Endpoints 295
15.2.3.4 Subgroup Analyses 296
15.2.3.5 Contamination 297
15.2.3.6 Estimates of Between-cluster Variability 297
15.3 Interpretation and Generalisability 298
15.3.1 Interpretation 298
15.3.2 Generalisability 299
15.3.3 Systematic Reviews 300
References 303
Index 309
|
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| id | DE-604.BV035907708 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:07:10Z |
| institution | BVB |
| isbn | 9781584888161 |
| language | English |
| lccn | 2008035804 |
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| series2 | Chapman & Hall, CRC interdisciplinary statistics series A Chapman & Hall book |
| spelling | Hayes, Richard J. Verfasser aut Cluster randomised trials Richard J. Hayes ; Lawrence H. Moulton Boca Raton [u.a.] CRC Press 2009 XXII, 315 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Chapman & Hall, CRC interdisciplinary statistics series A Chapman & Hall book Includes bibliographical references (p. 303-307) and index Clinical trials Cluster Analysis Cluster analysis Data Interpretation, Statistical Randomized Controlled Trials as Topic methods Moulton, Lawrence H. Verfasser (DE-588)139228268 aut http://www.loc.gov/catdir/toc/ecip0826/2008035804.html Table of contents only HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018765042&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Hayes, Richard J. Moulton, Lawrence H. Cluster randomised trials Clinical trials Cluster Analysis Cluster analysis Data Interpretation, Statistical Randomized Controlled Trials as Topic methods |
| title | Cluster randomised trials |
| title_auth | Cluster randomised trials |
| title_exact_search | Cluster randomised trials |
| title_full | Cluster randomised trials Richard J. Hayes ; Lawrence H. Moulton |
| title_fullStr | Cluster randomised trials Richard J. Hayes ; Lawrence H. Moulton |
| title_full_unstemmed | Cluster randomised trials Richard J. Hayes ; Lawrence H. Moulton |
| title_short | Cluster randomised trials |
| title_sort | cluster randomised trials |
| topic | Clinical trials Cluster Analysis Cluster analysis Data Interpretation, Statistical Randomized Controlled Trials as Topic methods |
| topic_facet | Clinical trials Cluster Analysis Cluster analysis Data Interpretation, Statistical Randomized Controlled Trials as Topic methods |
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