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Statistical Power Analysis in Research

Häftad, Engelska, 2015

AvHelena Chmura Kraemer,Christine M. Blasey

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With increased emphasis on helping readers understand the context in which power calculations are done, this Second Edition introduces a simple technique of statistical power analysis that allows researchers to compute approximate sample sizes and power for a wide range of research designs. Because the same technique is used with only slight modifications for different statistical tests, researchers can then easily compare the sample sizes required by different designs and tests to make cost-effective decisions in planning a study. These comparisons demonstrate important principles of design, measurement, and analysis that are rarely discussed in courses or textbooks, making this book a valuable instructional resource as well as a must-have guide for frequent reference.

Produktinformation

Utgivningsdatum2015-04-07
Mått152 x 228 x 12 mm
Vikt250 g
FormatHäftad
SpråkEngelska
Antal sidor160
Upplaga2
FörlagSAGE Publications
ISBN9781483319544

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Sociologi inom Samhälle och politik

Helena Chmura Kraemer is professor emerita of biostatistics in the Department of Psychiatry and Behavioral Sciences at Stanford University. She earned her BA in mathematics from Smith College, attended Manchester University on a Fulbright Scholarship, and received her PhD in statistics from Stanford University. Kraemer’s specific research interests include improvement to randomized clinical trial methodology, assessment of reliability and validity of diagnoses and clinical measurement, and developing mathematical models for specific problems in behavioral and clinical research. She has published extensively in the behavioral as well as statistical literature. Kraemer has received the Harvard Prize in Psychiatric Biostatistics and Epidemiology (2001), the Andrew C. Leon Distinguished Career Award (2014), an Honorary Doctor of Science from Wesleyan University (2014), and is a member of the Institute of Medicine, National Academy of Sciences (2003). In retirement, she continues to serve on several editorial boards, and consult on research projects. Christine Blasey is a professor in the PGSP-Stanford Consortium, an academic program taught by faculty drawn from Palo Alto University and the Stanford University School of Medicine Department of Psychiatry.

PREFACE1. The Rules of the GameExploratory StudiesHypothesis FormulationNull HypothesisDesignThe Statistical TestEffect Sizes: Critical, True, and EstimatedPower2. General ConceptsIntroduction to the Power TableStatistical Considerations3. The Pivotal Case: Interclass CorrelationThe Intraclass Correlation TestThe ANOVA Approach to Intraclass Correlation TestNormal Approximation to the Intraclass TheoryNon-Central tVariance RatiosConclusion4. Equality of Means: Z- and T-Test, Balanced ANOVASingle-Sample Test, Variance Known: z-testSingle-Sample t-testTwo Sample t-testAn Exercise in PlanningBalanced Analysis of Variance (ANOVA)5. Correlation CoefficientsIntraclass Correlation CoefficientProduct-Moment Correlation CoefficientRank Correlation CoefficientsYou Study What You Measure!6. Linear Regression AnalysisSimple Linear RegressionExperimental Design: Choosing the X-ValuesSimple Linear Moderation ExampleProblems: Collinearity and InteractionsMultiple Linear Regression7. Homogeneity of Variance TestsTwo Independent SamplesMatched Samples8. Binomial TestsSingle-Sample Binomial TestsTwo-Sample Binomial Tests9. Contingency Table AnalysisIntroductionThe I X J x^2-testAn Example of a 3 X 2 Contingency Table Analysis10. Wrap-Up