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Design and Analysis of Group-Randomized Trials [Kõva köide]

(Professor of Epidemiology, University of Minnesota School of Public Health, USA)
  • Formaat: Hardback, 480 pages, kõrgus x laius x paksus: 240x165x32 mm, kaal: 830 g, line figures and tables
  • Sari: Monographs in Epidemiology and Biostatistics 27
  • Ilmumisaeg: 19-Mar-1998
  • Kirjastus: Oxford University Press Inc
  • ISBN-10: 0195120361
  • ISBN-13: 9780195120363
Teised raamatud teemal:
  • Formaat: Hardback, 480 pages, kõrgus x laius x paksus: 240x165x32 mm, kaal: 830 g, line figures and tables
  • Sari: Monographs in Epidemiology and Biostatistics 27
  • Ilmumisaeg: 19-Mar-1998
  • Kirjastus: Oxford University Press Inc
  • ISBN-10: 0195120361
  • ISBN-13: 9780195120363
Teised raamatud teemal:
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-randomized trials, 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 also covers 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.

Arvustused

"This book is an important addition to any public health or medical library. It is well-written and much needed."--Doody's Journal

1. Introduction
3(16)
Examples
3(2)
Distinguishing Characteristics
5(1)
The Impact of These Characteristics
6(4)
Perspective
10(8)
Endnotes
18(1)
2. Planning the Trial
19(46)
The Research Question
19(1)
The Research Team
20(1)
The Research Design
21(25)
Variables of Interest and Their Measures
46(2)
The Intervention
48(2)
Preparing a Proposal
50(13)
Summary
63(1)
Endnotes
63(2)
3. Research Designs
65(12)
Main-Effect and Factorial Designs
65(1)
The Data-Collection Schedule
66(4)
Cross-sectional and Cohort Designs
70(2)
A Priori Matching and Stratification
72(2)
Summary
74(3)
4. Planning the Analysis
77(54)
Fundamentals
77(7)
Statistical Models
84(8)
Technical Issues Related to Statistical Models
92(12)
The Unit of Analysis in Statistical Models
104(3)
General Strategies for Model-Based Inference
107(8)
Randomization or Permutation Tests
115(2)
Computer Software
117(9)
Implementation Issues
126(2)
Summary
128(1)
Endnotes
129(2)
5. Analyses for Nested Cross-Sectional Designs
131(48)
Organization of the
Chapter
131(1)
Posttest-Only Control Group Design
132(8)
Pretest-Posttest Control Group Design
140(6)
Stratification or Matching in the Analysis
146(15)
Additional Baseline Or Follow-up Intervals
161(15)
Summary
176(1)
Endnotes
176(3)
6. Analyses for Nested Cohort Designs
179(44)
Posttest-Only Control Group Design
179(1)
Pretest-Posttest Control Group Design
179(11)
Stratification or Matching in the Analysis
190(22)
Additional Baseline or Follow-up Intervals
212(8)
Summary
220(1)
Endnotes
220(3)
7. Applications of Analyses for Nested Cross-Sectional Designs
223(72)
Organization of the
Chapter
223(4)
Posttest-Only Control Group Design
227(25)
Pretest-Pottest Control Group Design
252(9)
Stratification or Matching in the Analysis
261(5)
Additional Baseline or Follow-up Intervals
266(22)
Summary
288(2)
Endnotes
290(5)
8. Applications of Analyses for Nested Cohort Designs
295(54)
Posttest-Only Control Group Design
295(1)
Pretest-Posttest Control Group Design
296(23)
Stratification or Matching in the Analysis
319(7)
Additional Baseline or Follow-up Intervals
326(19)
Summary
345(1)
Endnotes
346(3)
9. Sample Size, Detectable Difference, and Power
349(66)
Factors That Determine Power
350(3)
Fundamentals of Power Analysis
353(11)
Extension to Other Design and Analysis Plans
364(32)
Examples
396(16)
Summary
412(1)
Endnotes
412(3)
10. Case Studies
415(30)
Nested Cross-Sectional Designs
415(15)
Nested Cohort Designs
430(13)
Summary
443(1)
Endnotes
443(2)
References 445(12)
Author Index 457(2)
Subject Index 459


David M. Murray has spent his career evaluating intervention programs designed to improve the public health. Beginning in the late 1980s, Dr. Murray focused on the design and analysis of group-randomized trials to assess the effect of an intervention. Dr. Murray served as the first Chair of the Community-Level Heath Promotion study section, which reviews many of the group-randomized trials submitted to NIH. After 35 years at the University of Minnesota, the University of Memphis, and the Ohio State University, Dr. Murray joined the NIH in September 2012, as the Associate Director for Prevention and Director of the Office of Disease Prevention. He is responsible for promoting and coordinating prevention research among and between NIH Institutes and Centers and other public and private entities.