Design and Analysis: A Researcher's Handbook

Cover
Contents
Preface
Part I Introduction
	1 Experimental Design
		1.1 Variables in Experimental Research
		1.2 Control in Experimentation
		1.3 Populations and Generalizing
		1.4 The Basic Experimental Designs
Part II Single-Factor Experiments
	2 Sources of Variability and Sums of Squares
		2.1 The Logic of Hypothesis Testing
		2.2 The Component Deviations
		2.3 Sums of Squares: Defining Formulas
		2.4 Sums of Squares: Computational Formulas
		Comment
		Exercises
	3 Variance Estimates and the F Ratio
		3.1 Completing the Analysis
		3.2 Evaluating the F Ratio
		3.3 Errors in Hypothesis Testing
		3.4 A Complete Numerical Example
		3.5 Unequal Sample Sizes
		Comment
		Exercises
	4 Analytical Comparisons Among Treatment Means
		4.1 The Need for Analytical Comparisons
		4.2 An Example of Planned Comparisons
		4.3 Comparisons Among Treatment Means
		4.4 Evaluating Contrasts with a t Test
		4.5 Orthogonal Contrasts
		4.6 Composite Contrasts Derived from Theory
		4.7 Comparing Three or More Means
		Exercises
	5 Analysis of Trend
		5.1 Analysis of Linear Trend
		5.2 Analysis of Quadratic Trend
		5.3 Higher-Order Trend Components
		5.4 Theoretical Prediction of Trend Components
		5.5 Planning a Trend Analysis
		5.6 Monotonic Trend Analysis
		Exercises
	6 Simultaneous Comparisons and the Control of Type I Errors
		6.1 Research Questions and Type I Error
		6.2 Planned Comparisons
		6.3 Restricted Sets of Contrasts
		6.4 Pairwise Comparisons
		6.5 Post-Hoc Error Correction
		Exercises
	7 The Linear Model and Its Assumptions
		7.1 The Statistical Model
		7.2 Sampling Bias and the Loss of Subjects
		7.3 Violations of Distributional Assumptions
		7.4 Dealing with Heterogeneity of Variance
		7.5 Contrasts with Heterogeneous Variance
		Exercises
	8 Effect Size, Power, and Sample Size
		8.1 Descriptive Measures of Effect Size
		8.2 Effect Sizes in the Population
		8.3 Power and Sample Size
		8.4 Determining Sample Size
		Comments
		8.5 Determining Power
		Comments
		Exercises
	9 Using Statistical Software
		9.1 Using the Programs
		9.2 An Example
		9.3 Hints, Cautions, and Advice
		Exercises
Part III Two-Way Factorial Experiments
	10 Introduction to Factorial Designs
		10.1 Basic Information from a Factorial Design
		10.2 The Concept of Interaction
		10.3 The Definition of an Interaction
		10.4 Further Examples of Interaction
		10.5 Measurement of the Dependent Variable
		Exercises
	11 The Overall Two-Factor Analysis
		11.1 Component Deviations
		11.2 Computations in the Two-Way Analysis
		11.3 A Numerical Example
		11.4 The Statistical Model
		11.5 Designs with a Blocking Factor
		11.6 Measuring Effect Size
		11.7 Sample Size and Power
		Exercises
	12 Detailed Analysis of Main Effects and Simple Effects
		12.1 Interpreting a Two-Way Design
		12.2 Comparisons for the Marginal Means
		12.3 Interpreting the Interaction
		12.4 Testing the Simple Effects
		12.5 Simple Comparisons
		12.6 Effect Sizes and Power for Simple Effects
		12.7 Controlling Familywise Type I Error
		Exercises
	13 The Analysis of Interaction Components
		13.1 Types of Interaction Components
		13.2 Analyzing Interaction Contrasts
		13.3 Orthogonal Interaction Contrasts
		13.4 Testing Contrast-by-Factor Interactions
		13.5 Contrasts Outside the Factorial Structure
		13.6 Multiple Tests and Type I Error
		Exercises
Part IV The General Linear Model
	14 The General Linear Model and Unbalanced Designs
		14.1 The General Linear Model
		14.2 The Two-Factor Analysis
		14.3 Averaging of Groups and Individuals
		14.4 Contrasts and Other Analytical Analyses
		14.5 Sensitivity to Assumptions
		Exercises
	15 The Analysis of Covariance
		15.1 Covariance and Linear Regression
		15.2 The Analysis of Covariance
		15.3 Adjusted Means
		15.4 Extensions of the Design
		15.5 Assumptions of the Analysis of Covariance
		15.6 Blocking and the Analysis of Covariance
		15.7 Preexisting Covariate Differences
		15.8 Effect Sizes, Power, and Sample Size
		Exercises
Part V Within-Subject Designs
	16 The Single-Factor Within-Subject Design: Basic Calculations
		16.1 The Analysis of Variance
		16.2 Analytical Comparisons
		16.3 Effect Size and Power
		16.4 Computer Analysis
		Exercises
	17 The Single-Factor Within Subject Design: Further Topics
		17.1 Advantages and Limitations
		17.2 The Statistical Model
		17.3 The Sphericity Assumption
		17.4 Incidental Effects
		17.5 Analyzing a Counterbalanced Design
		17.6 Missing Data in Within-Subject Designs
		Comment
		Exercises
	18 The Two-Factor Within-Subject Design
		18.1 The Overall Analysis
		18.2 Contrasts and Other Analytical Analyses
		18.3 Assumptions and the Statistical Model
		18.4 Counterbalancing of Nuisance Variables
		18.5 Effect Size and Sample Sizes
		Exercises
	19 The Two-Factor Mixed Design: Overall Analysis
		19.1 The Overall Analysis of Variance
		19.2 Statistical Model and Assumptions
		19.3 The Multivariate Alternative
		19.4 Missing Data and Unequal Sample Sizes
		19.5 Effect Sizes and Sample-Size Calculations
		Exercises
	20 The Two-Factor Mixed Design: Analytical Analyses
		20.1 Analysis of the Between-Subjects Factor
		20.2 Analysis of the Within-Subject Factor
		20.3 Analyses Involving the Interaction
		Exercises
Part VI Higher Factorial Designs and Other Extensions
	21 The Three-Factor Design: The Overall Analysis of Variance
		21.1 Components of the Three-Way Design
		21.2 The Three-Way Interaction
		21.3 Computational Procedures
		21.4 Effect Size, Sample Size, and Power
		Exercises
	22 The Three-Factor Design: Analytical Analysis
		22.1 Overview of the Analytical Analysis
		22.2 Analyses Involving the Cell Means
		22.3 Effects Based on Marginal Means
		22.4 Three-Factor Interaction Components
		22.5 Contrast-by-Factor Interactions
		22.6 Extension to Higher-Order Designs
		Exercises
	23 Within-Subject and Mixed Designs
		23.1 Varieties of Three-Factor Designs
		23.2 The Overall Analysis
		23.3 Two Examples of Mixed Designs
		23.4 Analytical Analyses in the A×B×C×S Design
		23.5 Analytical Analysis in Mixed Design
		Exercises
	24 Random Factors and Generalizing Results
		24.1 Statistical Generalization over Design Factors
		24.2 Random Factors and the F Ratio
		24.3 Error Terms in Random-Factor Designs
		24.4 Design Considerations with Random Factors
		Exercises
	25 Nested Factors
		25.1 Nested Factors
		25.2 Analysis of the Nested Designs
		25.3 Crossing a Nested Factor with Another Factor
		25.4 Planning a Study with Random Factors
		Exercises
	26 Higher-Order Designs
		26.1 Multifactor Experiments in the Behavioral Sciences
		26.2 Analyzing Higher-Order Designs
		Exercises
A Statistical Tables
	A.1 Critical Values of the F Distribution
	A.2 Critical Values of the t Distribution
	A.3 Coefficients of Orthogonal Polynomials
	A.4 Critical Values of the Šidák-Bonferroni t Statistic
	A.5 Critical Values for Dunnett\'s Test
	A.6 Critical Values of the Studentized Range Statistic
	A.7 Power Functions
B Abbreviated Answers to the Exercises
References
Subject Index
Author Index