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Preface | |
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Introduction | |
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Focus and Overview of Topics | |
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Some Basic Descriptive Statistics | |
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Summation Notation | |
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t Test for Independent Samples | |
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t Test for Dependent Samples | |
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Outliers | |
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SPSS and SAS Statistical Packages | |
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SPSS for Windows-Release 12.0 | |
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Data Files | |
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Data Entry | |
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Editing a Dataset | |
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Splitting and Merging Files | |
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Two Ways of Running Analyses on SPSS | |
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SPSS Output Navigator | |
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SAS and SPSS Output for Correlations, Descriptives, and t Tests | |
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Data Sets on Compact Disk | |
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Obtaining the Mean and Variance on the T1-30Xa Calculator | |
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One Way Analysis of Variance | |
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Introduction | |
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Rationale for ANOVA | |
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Numerical Example | |
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Expected Mean Squares | |
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MS[subscript w] and MS[subscript b] as Variances | |
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A Linear Model for the Data | |
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Assumptions in ANOVA | |
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The Independence Assumption | |
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ANOVA on SPSS and SAS | |
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Post Hoc Procedures | |
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Tukey Procedure | |
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The Scheffe Procedure | |
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Heterogeneous Variances and Unequal Group Sizes | |
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Measures of Association (Variance Accounted For) | |
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Planned Comparisons | |
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Test Statistic for Planned Comparisons | |
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Planned Comparisons on SPSS and SAS | |
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The Effect of an Outlier on an ANOVA | |
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Multivariate Analysis of Variance | |
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Summary | |
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Appendix | |
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Power Analysis | |
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Introduction | |
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t Test for Independent Samples | |
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A Priori and Post Hoc Estimation of Power | |
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Estimation of Power for One Way Analysis of Variance | |
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A Priori Estimation of Subjects Needed for a Given Power | |
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Ways of Improving Power | |
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Power Estimation on SPSSM ANOVA | |
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Summary | |
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Factorial Analysis of Variance | |
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Introduction | |
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Numerical Calculations for Two Way ANOVA | |
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Balanced and Unbalanced Designs | |
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Higher Order Designs | |
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A Comprehensive Computer Example Using Real Data | |
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Power Analysis | |
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Fixed and Random Factors | |
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Summary | |
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Doing a Balanced Two Way ANOVA With a Calculator | |
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Repeated Measures Analysis | |
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Introduction | |
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Advantages and Disadvantages of Repeated Measures Designs | |
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Single Group Repeated Measures | |
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Completely Randomized Design | |
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Univariate Repeated Measures Analysis | |
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Assumptions in Repeated Measures Analysis | |
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Should We Use the Univariate or Multivariate Approach? | |
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Computer Analysis on SAS and SPSS for Example | |
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Post Hoc Procedures in Repeated Measures Analysis | |
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One Between and One Within Factor-A Trend Analysis | |
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Post Hoc Procedures for the One Between and One Within Design | |
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One Between and Two Within Factors | |
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Totally Within Designs | |
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Planned Comparisons in Repeated Measures Designs | |
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Summary | |
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Simple and Multiple Regression | |
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Simple Regression | |
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Assumptions for the Errors | |
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Influential Data Points | |
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Multiple Regression | |
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Breakdown of Sum of Squares in Regression and F Test for Multiple Correlation | |
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Relationship of Simple Correlations to Multiple Correlation | |
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Multicollinearity | |
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Model Selection | |
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Two Computer Examples | |
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Checking Assumptions for the Regression Model | |
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Model Validation | |
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Importance of the Order of Predictors in Regression Analysis | |
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Other Important Issues | |
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Outliers and Influential Data Points | |
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Further Discussion of the Two Computer Examples | |
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Sample Size Determination for a Reliable Prediction Equation | |
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ANOVA as a Special Case of Regression Analysis | |
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Summary of Important Points | |
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The PRESS Statistic | |
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Analysis of Covariance | |
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Introduction | |
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Purposes of Covariance | |
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Adjustment of Posttest Means | |
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Reduction of Error Variance | |
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Choice of Covariates | |
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Numerical Example | |
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Assumptions in Analysis of Covariance | |
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Use of ANCOVA with Intact Groups | |
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Computer Example for ANCOVA | |
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Alternative Analyses | |
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An Alternative to the Johnson-Neyman Technique | |
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Use of Several Covariates | |
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Computer Example with Two Covariates | |
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Summary | |
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Hierarchical Linear Modeling | |
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Introduction | |
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Problems Using Single-Level Analyses of Multilevel Data | |
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Formulation of the Multilevel Model | |
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Two-Level Model-General Formulation | |
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HLM6 Software | |
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Two Level Example-Student and Classroom Data | |
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HLM Software Output | |
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Adding Level One Predictors to the HLM | |
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Addition of a Level Two Predictor to a Two Level HLM | |
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Evaluating the Efficacy of a Treatment | |
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Final Comments on Hlm | |
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Data Sets | |
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Clinical Data | |
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Alcoholics Data | |
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Sesame Street Data | |
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Headache Data | |
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Cartoon Data | |
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Attitude Data | |
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National Academy of Sciences Data | |
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Agresti Home Sales Data | |
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Statistical Tables | |
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Critical Values for F | |
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Percentile Points of Studentized Range Statistic | |
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Critical Values for Dunnett's Test | |
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Critical Values for F (max) Statistic | |
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Critical Values for Bryant-Paulson Procedure | |
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Power Tables | |
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Power of F Test at [alpha] = .05, u = 1 | |
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Power of F Test at [alpha] = .05, u = 2 | |
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Power of F Test at [alpha] = .05, u = 3 | |
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Power of F Test at [alpha] = .05, u = 4 | |
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Power of F Test at [alpha] = .10, u = 1 | |
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Power of F Test at [alpha] = .10, u = 2 | |
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Power of F Test at [alpha] = .10, u = 3 | |
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Power of F Test at [alpha] = .10, u = 4 | |
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References | |
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Answers to Selected Exercises | |
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Author Index | |
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Subject Index | |