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Computer-Assisted Research Design and Analysis
Barbara Tabachnick
Linda Fidell, both of California State University, Northridge

ISBN-10: 020532178X
ISBN-13: 9780205321780

Publisher: Prentice Hall
Copyright: 2001
Format: Cloth; 748 pp
Published: 06/07/2000
Status: Out of Print

Net price: $105.45 (What's this?)

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A comprehensive review of analyses of basic and complex ANOVA models through traditional approaches and multiple regression, integrating the most recent releases of MINITAB, SAS, SPSS, and SYSTAT.

In all chapters of this comprehensive text, both the basic model and its numerous complexities are presented along with discussions of effect size, relative efficiency and comparisons, illustrated by numerous examples. For each major model, the text provides tests for assumptions, a hand-worked example, and an example with real data including a write-up of the results using APA format. The text also provides data sets, syntax, and output for accomplishing numerous additional analyses through recent releases of MINITAB, SAS, SPSS and SYSTAT, often neglected in software manuals.

TECHNOLOGY ADVANTAGE: Inclusion of syntax and output from MINITAB, SAS, SPSS, and SYSTAT allows students to concentrate on the research question rather than on the specifics of the software program and provides the most thorough integration of text and software packages. The Companion Website contains datasets that accompany the text.

An example for each model, using real data and proceeding from assessment of assumptions through a Results section in APA format, provides students with step-by-step guidance for conducting and reporting an analysis.

Unique Chapter 10 on screening designs includes coverage of software to generate designs, familiarizing students with fractional factorials, Taguchi designs, Plackett-Burman designs, and response surface designs that are extremely useful in the early stages of research and/or in research with rare subjects.

Syntax and output for many of the complexities of analysis of covariance (Ch. 8), Latin square (Ch. 9), and random effects and nested models (Ch. 11) provide students with solutions for numerous problems that arise during research.

Presentation of both the traditional and multiple regression approaches to the basic model in Chapters 4-11 using the same example provides students with an alternative approach to ANOVA that offers much greater flexibility in understanding and analyzing a data set.

Preface.

1.Introduction.

The Nature of Research.

IVs and DVs. What Is an Experiment? What if It Isn't an Experiment? Relationship between Design and Analysis. Monitoring Processes to Aid in Experimental Design.

Types of Research Designs.

Randomized-Groups Designs. Repeated-Measures Designs. One-Way and Factorial Designs. Blocking Designs. Crossing and Nesting.

Types of Treatments.

Qualitative IVs. Quantitative IVs.

Outcome Measures.

Types of Outcome Measures. Number of Outcome Measures.

Overview of Research Designs.

Continuous Outcomes. Rank-Order Outcomes. Discrete Outcomes. Time as an Outcome.

Overview of Issues Encountered in Most Designs.

Statistical Inference. Power. Effect Size. Parameter Estimates. To Test or Not to Test.

Generalizing Results.

Computer Assistance.

Programs for Statistical Analysis. Programs for Designing Experiments.

Organization of the Book.

Choosing a Design: Some Guidelines.

Problem Sets.

2.Organizing, Describing, and Screening Data.

Organizing Data for a Computer.

Discrete, Continuous, and Ordinal Data. Randomized-Groups Designs. Repeated-Measures Designs.

Describing Data from One Variable.

Discrete Variables. Ordinal Variables. Continuous Variables.

Describing Relationships between Two Variables.

Both Variables Discrete. Both Variables Continuous. One Discrete and One Continuous Variable.

Problem Sets.

3.Basic ANOVA: Logic of Analysis and Tests of Assumptions.

Introduction.

Analysis of Variance.

The General Linear Model. Generation of a Data Set. The Basic Analysis.

The Regression Approach to ANOVA.

Bivariate Regression and Basic ANOVA. Why Bother?

Assumptions of Analysis.

Normality of Sampling Distribution of Means. Independence of Errors. Homogeneity of Variance. Absence of Outliers.

Other Recurring Issues.

Effect Size. Power. Comparisons. Orthogonality. Coding. Missing Values. Transformations.

Overview of Remaining Chapters.

Problem Sets.

4.One-Way Randomized-Groups Analysis of Variance, Fixed-Effects Designs.

General Purpose and Description.

Kinds of Research Questions.

Effect of the IV. Specific Comparisons. Parameter Estimates. Effect Sizes. Power.

Assumptions and Limitations.

Theoretical Issues. Practical Issues.

Fundamental Equations.

Allocation of Cases. Partition of Sources of Variance. Traditional ANOVA Approach (3 Levels). Regression Approach (3 Levels). Computer Analyses of Small-Sample One-Way Design.

Some Important Issues.

Effect Size. Power and Sample Size. Unequal Sample Sizes. Homogeneity of Variance. Specific Comparisons.

Complete Example of One-Way ANOVA.

Evaluation of Assumptions. Planned Trend Analysis for One-Way Randomized Groups Design.

Comparison of Programs.

SPSS Package. SAS System. SYSTAT System. MINITAB Programs.

Problem Sets.

5.Factorial Randomized-Groups, Fixed-Effects Designs.

General Purpose and Description.

Kinds of Research Questions.

Main Effects of the IV(s). Effects of Interactions among IV(s). Specific Comparisons. Parameter Estimates. Effect Sizes. Power.

Assumptions and Limitations.

Theoretical Issues. Practical Issues.

Fundamental Equations.

Allocation of Cases. Partition of Sources of Variance. Traditional ANOVA Approach (3 x 3). Regression Approach (3 x 3). Computer Analyses of Small-Sample Factorial Design.

Other Types of Randomized-Groups Designs.

Higher-Order Factorial Designs. Factorial Design with a Single Control.

Some Important Issues.

Interpreting Interactions. Effect Size. Power and Sample Size. Specific Comparisons. Unequal Sample Sizes.

Complete Example of Two-Way Randomized-Groups ANOVA.

Evaluation of Assumptions. Randomized-Groups Analysis of Variance.

Comparison of Programs.

SPSS Package. SAS System. SYSTAT System. MINITAB Programs.

Problem Sets.

6. Repeated-Measures Designs.

General Purpose and Description.

Kinds of Research Questions.

Effect of the IVs. Effect of Interactions among IVs. Parameter Estimates. Effect Sizes. Power. Specific Comparisons.

Assumptions and Limitations.

Theoretical Issues. Practical Issues.

Fundamental Equations.

One-Way Repeated-Measures ANOVA. Factorial Repeated-Measures Designs.

Types of Repeated Measures Designs.

Time as a Variable. Simultaneous Repeated Measures. Matched Randomized Blocks.

Some Important Issues.

Carryover Effects: Control of Extraneous Variables. Assumptions of Analysis: Independence of Errors, Sphericity, Additivity, and Compound Symmetry. Power, Sample Size, and Relative Efficiency. Effect Size. Missing Data. Specific Comparisons.

Complete Example of Two-Way Repeated-Measures ANOVA.

Evaluation of Assumptions. Planned Trend Analysis of Two-Way Repeated-Measures Design.

Comparison of Programs.

SPSS Package. SAS System. SYSTAT System. MINITAB Programs.

Problem Sets.

7. Mixed Randomized-Repeated Designs.

General Purpose and Description.

Kinds of Research Questions.

Effects of the IVs. Effects of Interactions among IVs. Parameter Estimates. Effect Sizes. Power. Specific Comparisons.

Assumptions and Limitations.

Theoretical Issues. Practical Issues.

Fundamental Equations.

Allocation of Cases. Partition of Sources of Variance. Traditional ANOVA for the Mixed Design. Regression Approach to the Mixed Design. Computer Analyses of Small-Sample Mixed Design.

Types of Mixed Designs.

The Pretest-Posttest Design. Expanding Mixed Designs.

Some Important Issues.

Comparisons on the Margins. Simple Main-Effects Analysis. Simple Comparisons. Interaction Contrasts. Comparisons through the Regression Approach.

Complete Example of Mixed Randomized-Repeated ANOVA.

Evaluation of Assumptions. Three-Way Mixed Randomized-Repeated ANOVA.

Comparison of Programs.

SPSS Package. SAS System. SYSTAT System. MINITAB Programs.

Putting It All Together for Factorial Designs.

Allocation of Cases. Assumptions of Analysis. Error Terms. Setup for Regression. Developing Computational Equations from Degrees of Freedom.

Problem Sets.

8. Analysis of Covariance.

General Purpose and Description.

Kinds of Research Questions.

Effect of the IV(s). Effect of Interactions among IVs. Effects of Covariates. Parameter Estimates. Effect Sizes. Power. Specific Comparisons.

Assumptions and Limitations.

Theoretical Issues. Practical Issues.

Fundamental Equations.

Allocation of Cases to Conditions. Partition of Sources of Variance. Traditional Approach with Three Levels and One Covariate. Computer Analyses of Small-Sample ANCOVA. Computer Analysis using Regression. Approach to ANCOVA.

Types of Designs Using Covariates.

Randomized-Groups Factorial. Repeated Measures.

Some Important Issues.

Multiple Covariates. Test of Homogeneity of Regression. Effect Size. Power. Adjusted Means. Specific Comparisons. Alternatives to ANCOVA.

Complete Examples of Analysis of Covariance.

One-Way Analysis of Covariance with Five Levels and One Covariate. Mixed Randomized-Groups and Repeated-Measures Analysis of Covariance.

Comparison of Programs.

SPSS Package. SAS System. SYSTAT System. MINITAB Program.

Problem Sets.

9. Latin-Square Designs.

General Purpose and Description.

Kinds of Research Questions.

Effects of the IV(s). Interactions among IVs. Parameter Estimates. Effect Sizes and Power. Specific Comparisons.

Assumptions and Limitations.

Theoretical Issues. Practical Issues.

Fundamental Equations.

Allocation of Cases. Partition of Sources of Variance. Traditional ANOVA Approach to 3 x 3 x 3 Latin Square. Regression Approach to 3 x 3 x 3 Latin Square. Computer Analyses of Small-Sample Latin-Square Example.

Types of Latin-Square Designs.

Replicated Randomized-Groups Designs. Replicated Repeated-Measures Designs. Less Commonly Encountered Designs.

Some Important Issues.

Sphericity in Repeated-Measures Designs. Choosing a Latin Square. Power, Effect Size, and Relative Efficiency. Specific Comparisons. Missing Data.

Complete Examples of Latin-Square ANOVA.

Complete Example of 4 x 4 x 4 Randomized-Groups Latin-Square Analysis. Complete Example of a Repeated-Measures Crossover Design with Multiple Trials.

Comparison of Programs.

The SPSS Package. The SAS System. The SYSTAT System. MINITAB Programs.

Problem Sets.

10. Screening and Other Incomplete Designs.

General Purpose and Description.

Kinds of Research Questions.

Effects of the IV(s). Effects of Interactions among IV(s). Parameter Estimates. Effect Sizes and Power. Specific Comparisons.

Assumptions and Limitations.

Theoretical Issues. Practical Issues.

Fundamental Equations.

Allocation of Cases. Partition of Variance. Regression Approach to a 25 Half-Factorial ANOVA. Computer Analyses of the Small-Sample 25 Half-Factorial ANOVA.

Types of Screening and Other Incomplete Designs.

Resolution of Incomplete Designs. Fractional-Factorial Designs. Plackett-Burman Designs. Taguchi Designs. Response-Surface Methodology. Optimal Designs.

Some Important Issues.

Generating Screening and Other Incomplete Designs. Choosing among Screening and Other Incomplete Designs.

Complete Example of a Central-Composite Design.

Generating the Design. Assumptions and Limitations. Three-Factor Central Composite Design.

Comparisons of Programs.

SAS Factex. NCSS Design of Experiments. MINITAB DOE.

Problem Sets.

11. Analysis of Variance with Random Effects.

General Purpose and Description.

Kinds of Research Questions.

Effects of Interactions among IV(s). Specific Comparisons. Parameter Estimates. Effect Sizes. Power.

Assumptions and Limitations.

Theoretical Issues. Practical Issues.

Fundamental Equations.

Allocation of Cases. Partition of Variance. Traditional ANOVA Approach (One Treatment Factor and One Level of Nesting). Regression Approach (One Treatment Factor and One Level of Nesting). Computer Analyses of Small Sample Nested Example.

Types of Designs with Random Effects.

Nested Designs. One-Way Random-Effects Design. Factorial Random-Effects Designs. Mixed Fixed-Random Designs.

Some Important Issues.

Error Terms in Random-Effects ANOVA. Alternative Strategies to ANOVA. Trend Analysis with Unequal Spacing. Homogeneity of Covariance.

Complete Example of Random-Effects ANOVA.

Evaluation of Assumptions. ANOVA for Doubly Nested Design.

Comparison of Programs.

SAS System. SPSS Package. SYSTAT System. MINITAB Programs.

Problem Sets.

Appendix A: Statistical Tables.

Critical Values of F Distribution.

Critical Values of x2 Distribution.

Critical Values of Studentized Range Statistic Distribution.

Critical Values of Dunnett's d-Statistic in Comparing Treatment Means with a Control (1-sided test).

Coefficients of Orthogonal Polynomials.

Critical Values of Fmax Distribution.

Appendix B: Research Designs for Complete Examples.

Facets in Fly's Eyes.

Bonding Strength of Periodontal Dressings.

Reaction Time to Identify Figures.

Auto Pollution Filter Noise.

Wear Testing of Fabric Samples.

Odors and Performance.

Processing Time for ANOVA.

Nambeware Polishing Times.

Chest Deceleration Injuries in Automobile Crashes.

Fat Content of Eggs.

Appendix C: Answers to Selected Problems.

References.

Index.

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Companion Website, 4/E
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