Introduction to Behavioral Research Methods

ISBN-10: 0205544142

ISBN-13: 9780205544141

Edition: 5th 2008

Authors: Mark R. Leary

List price: $171.00
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Book details

List price: $171.00
Edition: 5th
Copyright year: 2008
Publisher: Allyn & Bacon, Incorporated
Publication date: 8/20/2007
Binding: Hardcover
Pages: 464
Size: 8.00" wide x 10.00" long x 1.25" tall
Weight: 1.936
Language: English

Mark R. Leary, PhD, is Professor of Psychology at Wake Forest University. His research interests focus on social motivation and emotion, particularly processes involving the self. Dr. Leary has written or edited several previous books, including [i]Social Psychology and Dysfunctional Behavior[/i]; [i]Self Presentation: Impression Management and Interpersonal Behavior[/i]; [i]Social Anxiety[/i] (with R. M. Kowalski); [i]Interpersonal Rejection[/i]; and [i]Selfhood: Identity, Esteem, Regulation[/i]. He is also Editor of the journal [i]Self and Identity[/i]. June Price Tangney, PhD, is Professor of Psychology at George Mason University. She is coauthor (with Ronda Dearing) of [i]Shame and Guilt[/i] and coeditor (with Kurt Fischer) of [i]Self-Conscious Emotions: The Psychology of Shame, Guilt, Embarrassment, and Pride[/i]. Dr. Tangney is currently Associate Editor of [i]Self and Identity[/i] and Consulting Editor of [i]Journal of Personality and Social Psychology[/i], [i]Personality and Social Psychology Bulletin[/i], [i]Psychological Assessment[/i], [i]Journal of Social and Clinical Psychology[/i], and [i]Journal of Personality[/i]. Her research has been funded by the National Institute on Drug Abuse, the National Institute of Child Health and Human Development, and the John Templeton Foundation.

Research in the Behavioral Sciences
The Beginnings of Behavioral Research
Goals of Behavioral Research
The Value of Research to the Student
The Scientific Approach
Behavioral Science and Common Sense
Philosophy of Science
The Role of Theory in Science
Research Hypotheses
A Priori Predictions and Post Hoc Explanations
Conceptual and Operational Definitions
Proof and Disproof in Science
Strategies of Behavioral Research
Domains of Behavioral Science
A Preview
Behavioral Variability and Research
Variability and the Research Process
Variance: An Index of Variability
Systematic and Error Variance
Assessing the Strength of Relationships
Meta-Analysis: Systematic Variance across Studies
The Measurement of Behavior
Types of Measures
Scales of Measurement
Estimating the Reliability of a Measure
Estimating the Validity of a Measure
Fairness and Bias in Measurement
Approaches to Psychological Measurement
Observational Methods
Physiological Measures
Self-Report: Questionnaires and Interviews
Archival Data
Content Analysis
Descriptive Research
Types of Descriptive Research
Describing and Presenting Data
Correlational Research
The Correlation Coefficient
A Graphic Representation of Correlations
The Coefficient of Determination
Statistical Significance of r
Factors That Distort Correlation Coefficients
Correlation and Causality
Partial Correlation
Other Correlation Coefficients
Advanced Correlational Strategies
Predicting Behavior: Regression Strategies
Assessing Directionality: Cross-Lagged and Structural Equations Analysis
Uncovering Underlying Dimensions: Factor Analysis
Basic Issues in Experimental Research
Manipulating the Independent Variable
Assignment of Participants to Conditions
Experimental Control
Eliminating Confounds
Error Variance
Experimental Control and Generalizability: The Experimenter's Dilemma
Experimental Design
One-Way Designs
Factorial Designs
Main Effects and Interactions
Combining Independent and Subject Variables
Analyzing Experimental Data
An Intuitive Approach to Analysis
Hypothesis Testing
Analysis of Two-Group Experiments: The t-Test
Analyses of Matched-Subjects and Within-Subjects Designs
Analyzing Complex Designs
The Problem: Multiple Tests Inflate Type I Error
The Rationale behind ANOVA
How ANOVA Works
Follow-Up Tests
Between-Subjects and Within-Subjects ANOVAs
Multivariate Analysis of Variance
Experimental and Nonexperimental Uses of Inferential Statistics
Computer Analyses
Quasi-Experimental Designs
Pretest-Posttest Designs
Time Series Designs
Longitudinal Designs
Program Evaluation
Evaluating Quasi-Experimental
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