1.

Record Nr.

UNINA9910131022703321

Autore

Lui Kung-Jong

Titolo

Binary data analysis of randomized clinical trials with noncompliance [[electronic resource] /] / Kung-Jong Lui

Pubbl/distr/stampa

Chichester, West Sussex, United Kingdom, : John Wiley & Sons Inc., 2011

ISBN

1-283-40536-9

9786613405364

1-119-99160-9

1-119-99161-7

Descrizione fisica

1 online resource (332 p.)

Collana

Statistics in practice

Disciplina

615.5072/4

Soggetti

Clinical trials - Statistical methods

Drugs - Testing - Statistical methods

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Binary Data Analysis of Randomized Clinical Trials with Noncompliance; Contents; Preface; About the Author; 1 Randomized clinical trials with noncompliance: issues, definitions and problems of commonly used analyses; 1.1 Randomized encouragement design (RED); 1.2 Randomized consent designs; 1.2.1 Single-consent randomized design (SCRD); 1.2.2 Double-consent randomized design (DCRD); 1.3 Treatment efficacy versus programmatic effectiveness; 1.4 Definitions of commonly used terms and assumptions; 1.5 Most commonly used analyses for a RCT with noncompliance; Exercises

2 Randomized clinical trials with noncompliance under parallel groups design 2.1 Testing superiority; 2.2 Testing noninferiority; 2.2.1 Using the difference in proportions; 2.2.2 Using the ratio of proportions; 2.2.3 Using the odds ratio of proportions; 2.3 Testing equivalence; 2.3.1 Using the difference in proportions; 2.3.2 Using the ratio of proportions; 2.3.3 Using the odds ratio of proportions; 2.4 Interval estimation; 2.4.1 Estimation of the proportion difference; 2.4.2 Estimation of the proportion ratio; 2.4.3 Estimation of the odds ratio; 2.5 Sample size determination



2.5.1 Sample size calculation for testing superiority 2.5.2 Sample size calculation for testing noninferiority; 2.5.3 Sample size calculation for testing equivalence; 2.6 Risk model-based approach; 2.6.1 Constant risk additive model; 2.6.2 Constant risk multiplicative model; 2.6.3 Generalized risk additive model; 2.6.4 Generalized risk multiplicative model; Exercises; Appendix; 3 Randomized clinical trials with noncompliance in stratified sampling; 3.1 Testing superiority; 3.2 Testing noninferiority; 3.2.1 Using the difference in proportions; 3.2.2 Using the ratio of proportions

3.2.3 Using the odds ratio of proportions 3.3 Testing equivalence; 3.3.1 Using the difference in proportions; 3.3.2 Using the ratio of proportions; 3.3.3 Using the odds ratio of proportions; 3.4 Interval estimation; 3.4.1 Estimation of the proportion difference; 3.4.2 Estimation of the proportion ratio; 3.4.3 Estimation of the odds ratio; 3.5 Test homogeneity of index in large strata; 3.5.1 Testing homogeneity of the proportion difference; 3.5.2 Testing homogeneity of the proportion ratio; 3.5.3 Test homogeneity of the odds ratio; Exercises; Appendix

4 Randomized clinical trials with noncompliance under cluster sampling 4.1 Testing superiority; 4.2 Testing noninferiority; 4.2.1 Using the difference in proportions; 4.2.2 Using the ratio of proportions; 4.2.3 Using the odds ratio of proportions; 4.3 Testing equivalence; 4.3.1 Using the difference in proportions; 4.3.2 Using the ratio of proportions; 4.3.3 Using the odds ratio of proportions; 4.4 Interval estimation; 4.4.1 Estimation of the proportion difference; 4.4.2 Estimation of the proportion ratio; 4.4.3 Estimation of the odds ratio; 4.5 Sample size determination

4.5.1 Sample size calculation for testing superiority

Sommario/riassunto

It is quite common in a randomized clinical trial (RCT) to encounter patients who do not comply with their assigned treatment. Since noncompliance often occurs non-randomly, the commonly-used approaches, including both the as-treated (AT) and as-protocol (AP) analysis, and the intent-to-treat (ITT) (or as-randomized) analysis, are all well known to possibly produce a biased inference of the treatment efficacy. This book provides a systematic and organized approach to analyzing data for RCTs with noncompliance under the most frequently-encountered situations. These include parallel sampling,