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Summary
Table of Contents
Preface | p. xi |
Introduction | p. 1 |
Focus and Overview of Topics | |
Some Basic Descriptive Statistics | |
Summation Notation | |
t Test for Independent Samples | |
t Test for Dependent Samples | |
Outliers | |
SPSS and SAS Statistical Packages | |
SPSS for Windows-Release 12.0 | |
Data Files | |
Data Entry | |
Editing a Dataset | |
Splitting and Merging Files | |
Two Ways of Running Analyses on SPSS | |
SPSS Output Navigator | |
SAS and SPSS Output for Correlations, Descriptives, and t Tests | |
Data Sets on Compact Disk | |
Obtaining the Mean and Variance on the T1-30Xa Calculator | |
One Way Analysis of Variance | p. 45 |
Introduction | |
Rationale for ANOVA | |
Numerical Example | |
Expected Mean Squares | |
MS[subscript w] and MS[subscript b] as Variances | |
A Linear Model for the Data | |
Assumptions in ANOVA | |
The Independence Assumption | |
ANOVA on SPSS and SAS | |
Post Hoc Procedures | |
Tukey Procedure | |
The Scheffe Procedure | |
Heterogeneous Variances and Unequal Group Sizes | |
Measures of Association (Variance Accounted For) | |
Planned Comparisons | |
Test Statistic for Planned Comparisons | |
Planned Comparisons on SPSS and SAS | |
The Effect of an Outlier on an ANOVA | |
Multivariate Analysis of Variance | |
Summary | |
Appendix | |
Power Analysis | p. 105 |
Introduction | |
t Test for Independent Samples | |
A Priori and Post Hoc Estimation of Power | |
Estimation of Power for One Way Analysis of Variance | |
A Priori Estimation of Subjects Needed for a Given Power | |
Ways of Improving Power | |
Power Estimation on SPSSM ANOVA | |
Summary | |
Factorial Analysis of Variance | p. 123 |
Introduction | |
Numerical Calculations for Two Way ANOVA | |
Balanced and Unbalanced Designs | |
Higher Order Designs | |
A Comprehensive Computer Example Using Real Data | |
Power Analysis | |
Fixed and Random Factors | |
Summary | |
Doing a Balanced Two Way ANOVA With a Calculator | |
Repeated Measures Analysis | p. 181 |
Introduction | |
Advantages and Disadvantages of Repeated Measures Designs | |
Single Group Repeated Measures | |
Completely Randomized Design | |
Univariate Repeated Measures Analysis | |
Assumptions in Repeated Measures Analysis | |
Should We Use the Univariate or Multivariate Approach? | |
Computer Analysis on SAS and SPSS for Example | |
Post Hoc Procedures in Repeated Measures Analysis | |
One Between and One Within Factor-A Trend Analysis | |
Post Hoc Procedures for the One Between and One Within Design | |
One Between and Two Within Factors | |
Totally Within Designs | |
Planned Comparisons in Repeated Measures Designs | |
Summary | |
Simple and Multiple Regression | p. 219 |
Simple Regression | |
Assumptions for the Errors | |
Influential Data Points | |
Multiple Regression | |
Breakdown of Sum of Squares in Regression and F Test for Multiple Correlation | |
Relationship of Simple Correlations to Multiple Correlation | |
Multicollinearity | |
Model Selection | |
Two Computer Examples | |
Checking Assumptions for the Regression Model | |
Model Validation | |
Importance of the Order of Predictors in Regression Analysis | |
Other Important Issues | |
Outliers and Influential Data Points | |
Further Discussion of the Two Computer Examples | |
Sample Size Determination for a Reliable Prediction Equation | |
ANOVA as a Special Case of Regression Analysis | |
Summary of Important Points | |
The PRESS Statistic | |
Analysis of Covariance | p. 285 |
Introduction | |
Purposes of Covariance | |
Adjustment of Posttest Means | |
Reduction of Error Variance | |
Choice of Covariates | |
Numerical Example | |
Assumptions in Analysis of Covariance | |
Use of ANCOVA with Intact Groups | |
Computer Example for ANCOVA | |
Alternative Analyses | |
An Alternative to the Johnson-Neyman Technique | |
Use of Several Covariates | |
Computer Example with Two Covariates | |
Summary | |
Hierarchical Linear Modeling | p. 321 |
Introduction | |
Problems Using Single-Level Analyses of Multilevel Data | |
Formulation of the Multilevel Model | |
Two-Level Model-General Formulation | |
HLM6 Software | |
Two Level Example-Student and Classroom Data | |
HLM Software Output | |
Adding Level One Predictors to the HLM | |
Addition of a Level Two Predictor to a Two Level HLM | |
Evaluating the Efficacy of a Treatment | |
Final Comments on Hlm | |
Data Sets | p. 365 |
Clinical Data | |
Alcoholics Data | |
Sesame Street Data | |
Headache Data | |
Cartoon Data | |
Attitude Data | |
National Academy of Sciences Data | |
Agresti Home Sales Data | |
Statistical Tables | p. 399 |
Critical Values for F | |
Percentile Points of Studentized Range Statistic | |
Critical Values for Dunnett's Test | |
Critical Values for F (max) Statistic | |
Critical Values for Bryant-Paulson Procedure | |
Power Tables | p. 413 |
Power of F Test at [alpha] = .05, u = 1 | |
Power of F Test at [alpha] = .05, u = 2 | |
Power of F Test at [alpha] = .05, u = 3 | |
Power of F Test at [alpha] = .05, u = 4 | |
Power of F Test at [alpha] = .10, u = 1 | |
Power of F Test at [alpha] = .10, u = 2 | |
Power of F Test at [alpha] = .10, u = 3 | |
Power of F Test at [alpha] = .10, u = 4 | |
References | p. 423 |
Answers to Selected Exercises | p. 431 |
Author Index | p. 453 |
Subject Index | p. 457 |
Table of Contents provided by Ingram. All Rights Reserved. |
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