دانلود کتاب Design and Analysis: A Researcher's Handbook

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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