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Design and Analysis A Researcher's Handbook

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ISBN-10: 0135159415

ISBN-13: 9780135159415

Edition: 4th 2004 (Revised)

Authors: Geoffrey Keppel, Thomas D. Wickens

List price: $239.99
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Description:

The fourth edition ofDesign and Analysiscontinues to offer a readily accessible introduction to the designed experiment in research and the statistical analysis of the data from such experiments. Unique because it emphasizes the use of analytical procedures, this book is appropriate for all as it requires knowledge of only the most fundamental mathematical skills and little or no formal statistical background.Topics include: single- and two-factor designs with independent groups of subjects; corresponding designs with multiple observations; analysis of designs with unequal sample sizes; analysis of covariance; designs with three factors, including all combinations of between-subjects and…    
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Book details

List price: $239.99
Edition: 4th
Copyright year: 2004
Publisher: Prentice Hall PTR
Publication date: 1/21/2004
Binding: Hardcover
Pages: 624
Size: 7.25" wide x 9.50" long x 1.25" tall
Weight: 2.332
Language: English

Introduction
Experimental Design
Variables in Experimental Research
Control in Experimentation
Populations and Generalizing
The Basic Experimental Designs
Single-Factor Experiments
Sources of Variability and Sums of Squares
The Logic of Hypothesis Testing
The Component Deviations
Sums of Squares: Defining Formulas
Sums of Squares: Computational Formulas
Exercises
Variance Estimates and the F Ratio
Completing the Analysis
Evaluating the F Ratio
Errors in Hypothesis Testing
A Complete Numerical Example
Unequal Sample Sizes
Exercises
Analytical Comparisons Among Means
The Need for Analytical Comparisons
An Example of Planned Comparisons
Comparisons Among Treatment Means
Evaluating Contrasts with a t Test
Orthogonal Contrasts
Composite Contrasts Derived from Theory
Comparing Three or More Means
Exercises
Analysis of Trend
Analysis of Linear Trend
Analysis of Quadratic Trend
Higher-Order Trend Components
Theoretical Prediction of Trend Components
Planning a Trend Analysis
Monotonic Trend Analysis
Exercises
Simultaneous Comparisons
Research Questions and Type I Error
Planned Comparisons
Restricted Sets of Contrasts
Pairwise Comparisons
Post-Hoc Error Correction
Exercises
The Linear Model and Its Assumptions
The Statistical Model
Sampling Bias and the Loss of Subjects
Violations of Distributional Assumptions
Dealing with Heterogeneity of Variance
Contrasts with Heterogeneous Variance
Exercises
Effect Size, Power, and Sample Size
Descriptive Measures of Effect Size
Effect Sizes in the Population
Power and Sample Size
Determining Sample Size
Determining Power
Exercises
Using Statistical Software
Using the Programs
An Example
Hints, Cautions, and Advice
Exercises
Two-Way Factorial Experiments
Introduction to Factorial Designs
Basic Information from a Factorial Design
The Concept of Interaction
The Definition of an Interaction
Further Examples of Interaction
Measurement of the Dependent Variable
Exercises
The Overall Two-Factor Analysis
Component Deviations
Computations in the Two-Way Analysis
A Numerical Example
The Statistical Model
Designs with a Blocking Factor
Measuring Effect Size
Sample Size and Power
Exercises
Main Effects and Simple Effects
Interpreting a Two-Way Design
Comparisons for the Marginal Means
Interpreting the Interaction
Testing the Simple Effects
Simple Comparisons
Effect Sizes and Power for Simple Effects
Controlling Familywise Type I Error
Exercises
The Analysis of Interaction Components
Types of Interaction Components
Analyzing Interaction Contrasts
Orthogonal Interaction Contrasts
Testing Contrast-by-Factor Interactions
Contrasts Outside the Factorial Structure
Multiple Tests and Type I Error
Exercises
The General Linear Model
The General Linear Model
The General Linear Model
The Two-Factor Analysis
Averaging of Groups and Individuals
Contrasts and Other Analytical Analyses
Sensitivity to Assumptions
Exercises
The Analysis of Covariance
Covariance and Linear Regression
The Analysis of Covariance
Adjusted Means
Extensions of the Design
Assumptions of the Analysis of Covariance
Blocking and the Analysis of Covariance
Preexisting Covariate Differences
Effect Sizes, Power, and Sample Size
Exercises
Within-Subject Designs
The Single-Factor Within-Subject Design
The Analysis of Variance
Analytical Comparisons
Effect Size and Power
Computer Analysis
Exercises
Further Within-Subject Topics
Advantages and Limitations
The Statistical Model
The Sphericity Assumption
Incidental Effects
Analyzing a Counterbalanced Design
Missing Data in Within-Subject Designs
Exercises
The Two-Factor Within-Subject Design
The Overall Analysis
Contrasts and Other Analytical Analyses
Assumptions and the Statistical Model
Counterbalancing of Nuisance Variables
Effect Size and Sample Sizes
Exercises
The Mixed Design: Overall Analysis
The Overall Analysis of Variance
Statistical Model and Assumptions
The Multivariate Alternative
Missing Data and Unequal Sample Sizes
Effect Sizes and Sample-Size Calculations
Exercises
The Mixed Design: Analytical Analyses
Analysis of the Between-Subjects Factor
Analysis of the Within-Subject Factor
Analyses Involving the Interaction
Exercises
Higher Factorial Designs and Other Extensions
The Overall Three-Factor Design
Components of the Three-Way Design
The Three-Way Interaction
Computational Procedures
Effect Size, Sample Size, and Power
Exercises
The Three-Way Analytical Analysis
Overview of the Analytical Analysis
Analyses Involving the Cell Means
Effects Based on Marginal Means
Three-Factor Interaction Components
Contrast-by-Factor Interactions
Extension to Higher-Order Designs
Exercises
Within-Subject and Mixed Designs
Varieties of Three-Factor Designs
The Overall Analysis
Two Examples of Mixed Designs
Analytical Analyses in the A x B x C x S Design
Analytical Analysis in Mixed Designs
Exercises
Random Factors and Generalization
Statistical Generalization over Design Factors
Random Factors and the F Ratio
Error Terms in Random-Factor Designs
Design Considerations with Random Factors
Exercises
Nested Factors
Nested Factors
Analysis of the Nested Designs
Crossing a Nested Factor with Another Factor
Planning a Study with Random Factors
Exercises
Higher-Order Designs
Multifactor Experiments in the Behavioral Sciences
Analyzing Higher-Order Designs
Exercises
Statistical Tables
Critical Values of the F distribution
Critical Values of the t Distribution
Coefficients of Orthogonal Polynomials
Critical Values of the Sidak-Bonferroni t Statistic
Critical Values for Dunnett's Test
Critical Values of the Studentized Range Statistic
Power Functions
Abbreviated Answers to the Exercises
References
Subject Index
Author Index
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