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