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Statistical Power Analysis A Simple and General Model for Traditional and Modern Hypothesis Tests, Third Edition

ISBN-10: 1841697745
ISBN-13: 9781841697741
Edition: 3rd 2009 (Revised)
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Book details

List price: $41.95
Edition: 3rd
Copyright year: 2009
Publisher: Taylor & Francis Group
Publication date: 10/30/2008
Binding: Paperback
Pages: 224
Size: 6.00" wide x 8.75" long x 0.75" tall
Weight: 0.792
Language: English

Russell A. Barkley, PhD, ABPP, is Clinical Professor of Psychiatry at the Medical University of South Carolina and Research Professor of Psychiatry at the State University of New York Upstate Medical University in Syracuse. He was previously Director of Psychology and Professor of Psychiatry and Neurology at the University of Massachusetts Medical School. Dr. Barkley has published extensively on ADHD and has received numerous awards for his scientific and clinical contributions. He served as the principal investigator on the two large research projects reported in this volume. nbsp; Kevin R. Murphy, PhD, is founder and Director of the Adult ADHD Clinic of Central Massachusetts in Northborough. He was previously Director of the Adult ADHD Clinic and an Associate Professor of Psychiatry at the University of Massachusetts Medical School. He has published extensively on adults with ADHD and consults widely on the clinical diagnosis and management of ADHD in adults. Dr. Murphy served as the coinvestigator on the research study of clinic-referred adults with ADHD reported in this volume and conducted the clinical evaluations of all of the adults in that project. nbsp; Mariellen Fischer, PhD, is a pediatric neuropsychologist and Professor in the Division of Neuropsychology, Department of Neurology, Medical College of Wisconsin. Dr. Fischer has published numerous articles on ADHD, developmental psychopathology, and neuropsychology. She and Dr. Barkley have reported the earlier results of the Milwaukee longitudinal study of hyperactive children, the adult outcome of which is presented in this book. Dr. Fischer served as coinvestigator and the Milwaukee site principal investigator on the longitudinal study reported in this volume.

Preface
The Power of Statistical Tests
The Structure of Statistical Tests
The Mechanics of Power Analysis
Statistical Power of Research in the Social and Behavioral Sciences
Using Power Analysis
Hypothesis Tests Versus Confidence Intervals
Summary
A Simple and General Model for Power Analysis
The General Linear Model, the F Statistic, and Effect Size
The F Distribution and Power
Using the Noncentral F Distribution to Assess Power
Translating Common Statistics and ES Measures Into F
Defining Large, Medium, and Small Effects
Nonparametric and Robust Statistics
From F to Power Analysis
Analytic and Tabular Methods of Power Analysis
Using the One-Stop F Table
The One-Stop F Calculator
Summary
Power Analyses for Minimum-Effect Tests
Implications of Believing That the Nil Hypothesis Is Almost Always Wrong
Minimum-Effect Tests as Alternatives to Traditional Null Hypothesis Tests
Testing the Hypothesis That Treatment Effects Are Negligible
Using the One-Stop Tables to Assess Power to Test Minimum-Effect Hypotheses
Using the One-Stop F Calculator for Minimum-Effect Tests
Summary
Using Power Analyses
Estimating the Effect Size
Four Applications of Statistical Power Analysis
Calculating Power
Determining Sample Sizes
Determining the Sensitivity of Studies
Determining Appropriate Decision Criteria
Summary
Correlation and Regression
The Perils of Working With Large Samples
Multiple Regression
Power in Testing for Moderators
Why Are Most Moderator Effects Small?
Implications of Low Power in Tests for Moderators
Summary
t-Tests and the Analysis of Variance
The t-Test
Independent Groups t-Test
Traditional Versus Minimum-Effect Tests
One-Tailed Versus Two-Tailed Tests
Repeated Measures or Dependent t-Test
The Analysis of Variance
Which Means Differ?
Summary
Multifactor ANOVA Designs
The Factorial Analysis of Variance
Factorial ANOVA Example
Fixed, Mixed, and Random Models
Randomized Block ANOVA: An Introduction to Repeated-Measures Designs
Independent Groups Versus Repeated Measures
Complexities in Estimating Power in Repeated-Measures Designs
Summary
Split-Plot Factorial and Multivariate Analyses
Split-Plot Factorial ANOVA
Power for Within-Subject Versus Between-Subject Factors
Split-Plot Designs With Multiple Repeated-Measures Factors
The Multivariate Analysis of Variance
Summary
The Implications of Power Analyses
Tests of the Traditional Null Hypothesis
Tests of Minimum-Effect Hypotheses
Power Analysis: Benefits, Costs, and Implications for Hypothesis Testing
Direct Benefits of Power Analysis
Indirect Benefits of Power Analysis
Costs Associated With Power Analysis
Implications of Power Analysis: Can Power Be Too High?
Summary
References
Appendices
Author Index
Subject Index

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