Design and analysis of cluster randomization trials in health research:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Chichester
John Wiley
[2000]
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | X, 178 Seiten |
| ISBN: | 9780470711002 |
Internformat
MARC
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Datensatz im Suchindex
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| adam_text | Contents Acknowledgements Preface viii ix 1 Introduction 1.1 Why randomize clusters? 1.2 What is the impact of cluster randomization on the design and analysis of a trial? 1.3 Quantifying the effect of clustering 1.4 Randomized versus non-randomizedcomparisons 1.5 The unit of inference 1.6 Terminology: what’s in a name? 1 1 6 7 11 13 14 2 The historical development of cluster randomized trials 2.1 Randomized trials before 1950 2.2 Cluster randomized trials between 1950 and 1978 2.3 Cluster randomized trials since 1978 16 16 18 22 3 Issues arising in the planning of cluster randomization trials 3.1 Selecting interventions 3.2 Setting eligibility criteria 3.3 Measuring subject response 3.4 The most commonly used experimental designs 3.5 Factorial and crossover designs 3.6 Selecting an experimental design 3.7 The importance of cluster-level replication 3.8 Strategies for conducting successful trials 24 24 26 28 31 34 36 40 41 4 The role of informed consent and other ethical issues 4.1 The risk of harm 4.2 Informed consent 4.3 Subject blindness and informed consent 4.4 Randomized consent designs 4.5 Ethical issues and trial monitoring 43 44 45 48 49 50
vi Contents 5 Sample size estimation for cluster randomization designs 5.1 General issues of sample size estimation 5.2 The completely randomized design 5.2.1 Comparison of means 5.2.2 Subsample size and statistical efficiency 5.2.3 Comparison of proportions 5.2.4 Comparison of incidence rates 5.3 The matched-pair design 5.3.1 Comparison of means 5.3.2 Comparison of proportions 5.3.3 Comparison of incidence rates 5.4 The stratified design 5.4.1 Comparison of means 5.4.2 Comparison of proportions 5.5 Issues involving losses to follow-up 5.6 Strategies for achieving desired power 52 53 56 56 60 62 64 65 66 67 69 70 70 70 74 76 6 Analysis of binary outcomes 6.1 Selecting the unit of analysis 6.2 The completely randomized design 6.2.1 Comparison of proportions 6.2.1.1 Standard Pearson chi-square test 6.2.1.2 Cluster-level analyses Two-sample i-test comparing average values of the event rates Non-parametric approaches 6.2.1.3 Individual-level analyses Adjusted chi-square approach Ratio estimator approach Parametric modelling Generalized estimating equations approach 6.2.1.4 Summary of results 6.2.2 Confidence interval construction 6.2.3 Adjusting for covariates 6.2.4 Analysis strategies for trials with a small number of clusters per group 6.3 The matched-pair design 6.3.1 Comparison of proportions 6.3.1.1 Standard Mantel-Haenszel chi-square test 6.3.1.2 Liang’s test procedure 6.3.1.3 Paired t-test 6.3.1.4 Non-parametric approaches 6.3.1.5 Summary of results 6.3.2 Confidence interval construction 6.3.3 Adjusting for covariates 6.4 The stratified design 79 80 84 84 85 87 87 88 90
90 91 92 93 95 96 ՛ 97 100 100 100 102 102 102 104 105 106 107 108
Contents vii 7 Analysis of quantitative outcomes 7.1 The completely randomized design 7.1.1 Comparison of two means 7.1.1.1 Standard two sample Mest 7.1.1.2 Cluster-level analyses 7.1.1.3 Individual-level analyses Adjusted two-sample Mest Mixed-effects linear regression models 7.1.2 Adjusting for covariates 7.2 The matched-pair design 7.2.1 Comparison of means 7.2.2 Adjusting for covariates 7.3 The stratified design 111 111 111 113 114 114 114 116 120 122 122 123 125 8 Analysis of count, time to event and categorical outcomes 8.1 Count and time to event data 8.1.1 The completely randomized design 8.1.1.1 Standard methods of analysis 8.1.1.2 Cluster-level analyses 8.1.1.3 Extensions of Poisson regression Ratio estimator approach Parametric models Generalized estimating equations approach 8.1.1.4 Extensions of the Cox proportional hazards model 8.1.2 Matched-pair and stratified designs 8.2 Categorical data 128 129 129 129 132 132 132 133 134 135 138 139 9 Reporting of cluster randomization trials 9.1 Reporting of study design 9.2 Reporting of study results 141 141 145 References 152 Index 175
|
| adam_txt |
Contents Acknowledgements Preface viii ix 1 Introduction 1.1 Why randomize clusters? 1.2 What is the impact of cluster randomization on the design and analysis of a trial? 1.3 Quantifying the effect of clustering 1.4 Randomized versus non-randomizedcomparisons 1.5 The unit of inference 1.6 Terminology: what’s in a name? 1 1 6 7 11 13 14 2 The historical development of cluster randomized trials 2.1 Randomized trials before 1950 2.2 Cluster randomized trials between 1950 and 1978 2.3 Cluster randomized trials since 1978 16 16 18 22 3 Issues arising in the planning of cluster randomization trials 3.1 Selecting interventions 3.2 Setting eligibility criteria 3.3 Measuring subject response 3.4 The most commonly used experimental designs 3.5 Factorial and crossover designs 3.6 Selecting an experimental design 3.7 The importance of cluster-level replication 3.8 Strategies for conducting successful trials 24 24 26 28 31 34 36 40 41 4 The role of informed consent and other ethical issues 4.1 The risk of harm 4.2 Informed consent 4.3 Subject blindness and informed consent 4.4 Randomized consent designs 4.5 Ethical issues and trial monitoring 43 44 45 48 49 50
vi Contents 5 Sample size estimation for cluster randomization designs 5.1 General issues of sample size estimation 5.2 The completely randomized design 5.2.1 Comparison of means 5.2.2 Subsample size and statistical efficiency 5.2.3 Comparison of proportions 5.2.4 Comparison of incidence rates 5.3 The matched-pair design 5.3.1 Comparison of means 5.3.2 Comparison of proportions 5.3.3 Comparison of incidence rates 5.4 The stratified design 5.4.1 Comparison of means 5.4.2 Comparison of proportions 5.5 Issues involving losses to follow-up 5.6 Strategies for achieving desired power 52 53 56 56 60 62 64 65 66 67 69 70 70 70 74 76 6 Analysis of binary outcomes 6.1 Selecting the unit of analysis 6.2 The completely randomized design 6.2.1 Comparison of proportions 6.2.1.1 Standard Pearson chi-square test 6.2.1.2 Cluster-level analyses Two-sample i-test comparing average values of the event rates Non-parametric approaches 6.2.1.3 Individual-level analyses Adjusted chi-square approach Ratio estimator approach Parametric modelling Generalized estimating equations approach 6.2.1.4 Summary of results 6.2.2 Confidence interval construction 6.2.3 Adjusting for covariates 6.2.4 Analysis strategies for trials with a small number of clusters per group 6.3 The matched-pair design 6.3.1 Comparison of proportions 6.3.1.1 Standard Mantel-Haenszel chi-square test 6.3.1.2 Liang’s test procedure 6.3.1.3 Paired t-test 6.3.1.4 Non-parametric approaches 6.3.1.5 Summary of results 6.3.2 Confidence interval construction 6.3.3 Adjusting for covariates 6.4 The stratified design 79 80 84 84 85 87 87 88 90
90 91 92 93 95 96 ՛ 97 100 100 100 102 102 102 104 105 106 107 108
Contents vii 7 Analysis of quantitative outcomes 7.1 The completely randomized design 7.1.1 Comparison of two means 7.1.1.1 Standard two sample Mest 7.1.1.2 Cluster-level analyses 7.1.1.3 Individual-level analyses Adjusted two-sample Mest Mixed-effects linear regression models 7.1.2 Adjusting for covariates 7.2 The matched-pair design 7.2.1 Comparison of means 7.2.2 Adjusting for covariates 7.3 The stratified design 111 111 111 113 114 114 114 116 120 122 122 123 125 8 Analysis of count, time to event and categorical outcomes 8.1 Count and time to event data 8.1.1 The completely randomized design 8.1.1.1 Standard methods of analysis 8.1.1.2 Cluster-level analyses 8.1.1.3 Extensions of Poisson regression Ratio estimator approach Parametric models Generalized estimating equations approach 8.1.1.4 Extensions of the Cox proportional hazards model 8.1.2 Matched-pair and stratified designs 8.2 Categorical data 128 129 129 129 132 132 132 133 134 135 138 139 9 Reporting of cluster randomization trials 9.1 Reporting of study design 9.2 Reporting of study results 141 141 145 References 152 Index 175 |
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| spelling | Donner, Allan 19XX- Verfasser (DE-588)1249408326 aut Design and analysis of cluster randomization trials in health research Allan Donner ; Neil KLar Chichester John Wiley [2000] ©2000 X, 178 Seiten txt rdacontent n rdamedia nc rdacarrier Randomized Controlled Trials - methods Cluster Analysis Research Design Clinical trials gtt Medizin Group-randomized trials Medicine Research Methodology Randomized Controlled Trials as Topic methods Klar, Neil 19XX- Verfasser (DE-588)1249408474 aut Äquivalent London: Arnold, 2000 Druck-Ausgabe 0-340-69153-0 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=033053274&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Donner, Allan 19XX- Klar, Neil 19XX- Design and analysis of cluster randomization trials in health research Randomized Controlled Trials - methods Cluster Analysis Research Design Clinical trials gtt Medizin Group-randomized trials Medicine Research Methodology Randomized Controlled Trials as Topic methods |
| title | Design and analysis of cluster randomization trials in health research |
| title_auth | Design and analysis of cluster randomization trials in health research |
| title_exact_search | Design and analysis of cluster randomization trials in health research |
| title_exact_search_txtP | Design and analysis of cluster randomization trials in health research |
| title_full | Design and analysis of cluster randomization trials in health research Allan Donner ; Neil KLar |
| title_fullStr | Design and analysis of cluster randomization trials in health research Allan Donner ; Neil KLar |
| title_full_unstemmed | Design and analysis of cluster randomization trials in health research Allan Donner ; Neil KLar |
| title_short | Design and analysis of cluster randomization trials in health research |
| title_sort | design and analysis of cluster randomization trials in health research |
| topic | Randomized Controlled Trials - methods Cluster Analysis Research Design Clinical trials gtt Medizin Group-randomized trials Medicine Research Methodology Randomized Controlled Trials as Topic methods |
| topic_facet | Randomized Controlled Trials - methods Cluster Analysis Research Design Clinical trials Medizin Group-randomized trials Medicine Research Methodology Randomized Controlled Trials as Topic methods |
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