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Design and Analysis of Group-Randomized Trials

9780195120363
478,80 zł
454,86 zł Zniżka 23,94 zł Brutto
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Opis
This is the first comprehensive text on the design and analysis of group-randomized trials. It It collects information previously scattered among journals and texts in a variety of disciplines, and, in addition, presents much new material not available elsewhere. The book has been written to help those involved in these trials improve their ability to plan, fund, conduct, analyse, and interpret them, and to give students a detailed understanding of the field. Group-randomized trials are comparative studies in which the units of assignment are identifiable groups and the units of observation are members of those groups. The positive intraclass correlation expected among the members of each group poses unique and challenging issues for the design and analysis of these trials and separates them from the traditional clinical trial. After reviewing the underlying issues, Murray presents the research designs that are most widely used in group-randomizedtrials, together with their strengths, weaknesses, and appropriate applications. He describes the many approaches to analysis that are now available, presents mixed-model regression analyses appropriate to each design, and illustrates them using data from the Minnesota Heart Health Program. He alsocovers methods for estimating sample size, detectable difference, and power. This volume is not limited only to a conceptual treatment of the issues and solutions. It offers a review of the practical applications in a series of case studies, examples, and problems.
Szczegóły produktu
OUP USA
83862
9780195120363
9780195120363

Opis

Rok wydania
1998
Numer wydania
1
Oprawa
twarda
Liczba stron
478
Wymiary (mm)
172 x 244
Waga (g)
1011
  • Introduction; Planning the Trials; Research Design; Planning the Analysis; Analysis for Nested Cross-Sectional Designs; Analysis for Nested-Cohort Designs; Applications of Analyses for Nested Cross-Sectional Designs; Applications of Analyses for Nested-Cohort Designs; Sample Size, Detectable Difference and Power; Case Studies;
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