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Contents Preface Part I. Conceptual and Ethical Foundations 1. The Spirit of Behavioral Research Science and the Search for Knowledge What Do Behavioral Researchers Really Know? Social Constructionism Contextualism/Perspectivism Evolutionary Epistemology Peirce's Four Ways of Knowing Rhetoric, Perceptibility, and Aesthetics Limitations of the Four Supports of Conviction Behavioral Research Defined Three Broad Research Orientations The Descriptive Research Orientation The Relational Research Orientation The Experimental Research Orientation Empirical Principles as Probabilistic Assertions Orienting Habits of Good Scientific Practice 2. Contexts of Discovery and Justification Inspiration and Explanation Theories and Hypotheses Sources of Inspiration and Insight Serendipity in Behavioral Research Molding Ideas Into Working Hypotheses Positivism, Falsificationism, and Conventionalism Type I and Type II Decision Errors Statistical Significance and the Effect Size Two Families of Effect Sizes Interval Estimates Around Effect Sizes Summing Up 3. Ethical Considerations, Dilemmas, and Guidelines Puzzles and Problems A Delicate Balancing Act Historical Context of the APA Code The Belmont Report, Federal Regulations, and the IRB Principle I: Respect for Persons and Their Autonomy Principle II: Beneficence and Nonmaleficence Principle III: Justice Principle IV: Trust Principle V: Fidelity and Scientific Integrity Costs, Utilities, and Institutional Review Boards Scientific and Societal Responsibilities Part II. Operationalization and Measurement of Dependent Variables 4. Reliability and Validity of Measurements Random and Systematic Error Assessing Stability and Equivalence Internal-Consistency Reliability and Spearman-Brown KR20 and Cronbach's Alpha Effective Reliability of Judges Effective Cost of Judges Effective Cost of Items Interrater Agreement and Reliability Cohen's Kappa Replication in Research Validity Criteria in Assessment Convergent and Discriminant Validity Test Validity, Practical Utility, and the Taylor-Russell Tables Relationship of Validity to Reliability 5. Observations, Judgments, and Composite Variables Observing, Classifying, and Evaluating Observing While Participating Maximizing Credibility and Serendipity Organizing and Sense-Making in Ethnographic Research Interpreter and Observer Biases Unobtrusive Observations and Nonreactive Measurements Selecting the Most Appropriate Judges Choosing the Number of Response Alternatives Effects of Guessing and Omissions on Accuracy Intrinsic Factors and the Level of Accuracy Applications of Categorical Judgments Category Scales and Rating Scales Numerical, Graphic, and Magnitude Ratings Rating Biases and Their Control Bipolar Versus Unipolar Scales Forming Composite Variables Forming Multiple Composites Quantifying the Clarity of Composites 6. Questionnaires, Interviews, and Diaries Concerns About Self-Report Data Open-Ended Versus Structured Items Critical Incident Technique Stages in Developing Interview Protocols Research Interviews By Telephone Developing Research Questionnaires Defensiveness, Inconsistency, and Yea-Saying Cross-Cultural Questionnaire and Interview Research One-Dimensional and Multidimensional Attitude Scales Semantic Differentials for Attitudinal Meaning Q-Sorts for Subjectivity Ratings Likert Method of Item Analysis Thurstone Equal-Appearing Intervals Method Memory and the Use of Self-Recorded Diaries Part III. The Logic of Research Designs 7. Randomized Controlled Experiments and Causal Inference Experimentation in Science Randomized Experimental Designs Characteristics of Randomization The Philosophical Puzzle of Causality Contiguity, Priority, and Constant Conjunction Four Types of Experimental Control Mill's Methods of Agreement and Difference Between-Group Designs and Mill's Joint Method Independent, Dependent, and Moderator Variables Solomon's Extended Control Group Design Threats to Internal Validity Threats to External Validity Statistical Conclusion and Construct Validity Subject and Experimenter Artifacts Demand Characteristics and Their Control Interactional Experimenter Effects Experimenter Expectancy Effects and Their Control Concluding Commentary 8. Nonrandomized Research and Functional Relationships Nonrandomized and Quasi-Experimental Studies Nonequivalent Groups and Historical Controls Interrupted Time-Series and ARIMA Single-Case Experimental Designs Cross-Lagged Correlational Designs Invisible Variables and the Mediation Problem Path Analysis and Causal Inference The Cohort in Longitudinal Research Different Forms of Cohort Studies Subclassification on Propensity Scores Multiple Confounding Covariates 9. Randomly and Nonrandomly Selected Sampling Units Sampling a Small Part of the Whole Bias and Instability in Surveys Simple Random Sampling Plans Improving Accuracy in Random Sampling Confidence Intervals for Population Estimates Speaking of Confidence Intervals Other Selection Procedures Nonresponse Bias and Its Control Studying the Volunteer Subject Characteristics of the Volunteer Subject Implications for the Interpretation of Research Findings Situational Correlates and the Reduction of Volunteer Bias The Problem of Missing Data Procedures for Dealing With Missing Data Part IV. Fundamentals of Data Analysis 10. Describing, Displaying, and Exploring Data Descriptions of Sampling Units Frequency Diagrams and Stem-and-Leaf Displays Box Plots Comparing Distributions Back to Back Measures of Central Tendency Measures of Spread The Normal Distribution Standard Scores Data Not Distributed Normally Precision of Estimating Population Means Defining Outliers Coping With Outliers Exploring the Data 11. Correlation Pearson r Proportion of Variance Interpretation of Correlation Binomial Effect Size Display Confidence Intervals for Effect Size Correlations Small Correlations, But Important Effects Counternull Values of Effect Sizes Spearman Rank Correlation Ranks as a Transformation Observations of Disproportionate Influence Point-Biserial Correlation Exact Tests for Rho Phi Coefficient Curvilinear (Quadratic) Correlation Five Product-Moment Correlations Comparing Correlations Considering Third Variables Effects of Variability on Correlations 12. Statistical Power and Effect Size Revisited Why Assess Statistical Power? The Neglect of Statistical Power The requivalent Statistic Cohen's Multipurpose Power Tables The t Test For Comparing Two Means The Significance of a Product-Moment r Differences Between Correlation Coefficients The Test That a Proportion is .50 The Difference Between Proportions The Focused Chi-Square Test F Tests for Focused Comparisons Additional Strategies for Improving Power Part V. One-Way Designs 13. Comparing Means by Standard t Tests Gosset and the t Test Two Components of t Tests Maximizing t Effect Sizes and Adjustments for Unequal Sample Sizes Interpreting the Independent t Computing the Independent t Reporting the Results t Tests for Nonindependent Samples Effect Size and Study Size Components of Nonindependent t Assumptions Underlying t Tests Nonparametric Procedures The Bootstrap, the Jackknife, and Permutation Tests 14. Analysis of Variance and the F Test The F Test and the t Test The Analysis of "Variances" Illustration of an Omnibus F Dividing Up the Total Variance ANOVA Summary Tables Distributions of F After the Omnibus F Protecting Against "Too Many t Tests" Bonferroni Procedures Bonferroni Tolerance Value Comparing Two Independent Variabilities Illustration Using Transformations Comparing Two Correlated Variabilities Comparing Three or More Independent Variabilities Comparing Three or More Correlated Variabilities Summary of Procedures for Comparing Variabilities 15. One-Way Contrast Analyses Focusing Our Questions and Statistical Tests Contrast F Tests on Original Data Contrast t Tests on Original Data Carving Contrasts Out of Published Data Orthogonal Contrasts Nonorthogonal Contrasts Effect Size Indices for Contrasts The BESD and the Binomial Effect-Size Correlation Overview of the Four Effect Size Indices Comparing Competing Contrasts Combining Competing Contrasts Optimal Design and the Allocation of Sample Sizes Part VI. Factorial Designs 16. Factorial Analysis of Variance Confronting Persistent Misunderstandings An Economy of Design Effects and the Structure of ANOVA Individual Differences as Error The Table of Variance Testing the Grand Mean by t and F Unweighted Means Analysis for Equal or Unequal Sample Sizes Effects on F of Unequal Sample Sizes Unequal Sample Sizes and Contrasts Transcending Factorial Structure Using Contrasts Higher-Order Factorial Designs Blocking and the Increase of Power Blocking and the Analysis of Covariance Transforming Data to Remove Interactions 17. Interaction Effects in Analysis of Variance The Interpretation of Interaction Crossed and Uncrossed Combinations of Group Means Illustration of Mean Polishing Constructing Tables of Predicted Means Studying Interactions in Two-way Tables Three-way Factorial Designs Defining Three-way Interactions Further Notes on Interpretation Simplifying Complex Tables of Residuals Illustration of a Five-way Interaction A Note on Complexity 18. Repeated Measures in Analysis of Variance Use of Repeated Observations Basic Computations Fixed and Random Effects Error Terms in the Four Basic Combinations Latin Squares and Counterbalancing Analysis of Latin Squares Some Latin Squares May Be Better Than Others Other Counterbalancing Designs Three or More Factors Two Within-Subjects Factors Aggregating Error Terms Three Within-Subjects Factors Fixed or Random Factors Did Repeated Measures Help? The Intraclass r Revisited Composite Variables and Additional Assumptions Contrasts in Repeated Measures Hierarchically Nested Designs The Choice of Error Terms Part VII. Additional Topics in Data Analysis 19. Significance Testing and Association in Tables of Counts Table Analysis and Chi-Square The 1-df Chi-Square Test Larger Tables of Counts Distributions of Chi-Square Procedures for Larger Contingency Tables Subdividing Tables to Test Specific Hypotheses Fisher Exact Probability Test Strengthening the Fisher Exact Test Adjustments for in 2 x 2 Tables Complete Partitioning of Larger Tables The Corner-Cells Test Subtable Contrasts in Proportions Alternative Analyses for Smaller Sample Studies Standardizing Row and Column Totals Odds Ratio, Relative Risk, Risk Difference, and Phi One-Sample Tables of Counts Multiple-Choice-Type Data and the Proportion Index 20. Multivariate Data Analysis Background Redescribing Relationships Within Sets of Variables Cluster Analysis for Redescription Principal Components Analysis for Redescription Improving Interpretation By Rotation Psychometric Applications of Principal Components Analysis Alternatives for the Redescription of Variables Multidimensional Scaling Illustration Relationships Among Sets of Variables 21 Meta-Analysis: Comparing and Combining Research Results Statistical Analysis of Statistical Analyses Criticisms of Meta-Analysis Interpreting Two or More Studies Comparing Two Significance Levels Comparing Two Effect Size Correlations Combining Two Significance Levels Combining Two Effect Size Correlations Overall Comparisons of Three or More Studies Focused Comparisons of Three or More Studies Combining Three or More p Levels Combining Three or More Effect Size Correlations Results That Are Not Independent The File Drawer Problem An Eye to Variability Part VIII. Appendices A: List of Numbered Equations B: Statistical Tables Glossary References Indexes Name Index Subject Index (pages with the definitions of terms will be indicated in boldface)

Library of Congress Subject Headings for this publication:

Psychology -- Research -- Methodology.