Beginning Behavioral Research: A Conceptual Primer, 6/E
Ralph L. Rosnow, Temple University
Robert Rosenthal, University of California, Riverside

ISBN-10: 0136128750
ISBN-13: 9780136128755

Publisher: Prentice Hall
Copyright: 2008
Format: Cloth; 480 pp
Published: 04/25/2007

Suggested retail price: $125.20
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For classes involving introductory Research or Experimental Methods.

 

This successful introduction to behavioral research methods provides step-by-step guidance through the processes of planning an empirical study, analyzing and interpreting data, and reporting findings and conclusions.

 

When Beginning Behavioral Research was created, it was conceived as an undergraduate text for students, who, as part of a course in research methods, are required to plan an empirical study, to analyze and interpret the data, and to present their findings and conclusions in a written report. With this in mind, however, through their years in the field the authors found that all research methods are limited in some ways, and therefore it is essential not to foreclose on the use of tools and techniques that enable the study of phenomena from more than one vantage point. By examining different scientific methods, theories, and units of analysis - rather than any single one - the authors are able to give students a broad base of scientific thinking that will, they believe, encourage the idea that each generation of researchers builds on the important findings of previous researchers in a chain of discovery and understanding. 

How do you introduce your students to the study of behavioral research?

  • Features a logical, linear sequence corresponding to the steps involved in conceptualizing and conducting an empirical study and then analyzing and reporting the results. The beginning researcher is led step by step through the following process:

1. Crafting a research idea that can be empirically tested. (Chapters 1-3)

2. Choosing methods of data collection and measurement. (Chapters 4-6)

3. Designing and implementing the research study. (Chapters 7-9)

4. Approaching the research data. (Chapters 10-12)

5. Testing hypotheses and exploring the results. (Chapters 13-15 and Appendix C)

6. Reporting the research project in a paper or in a poster. Writing up the research findings and conclusions in the style of the APA publication manual and preparing a poster (Appendix A)

 - For a detailed chapter by chapter walkthrough, see below. -

Do your students have access to the most up-to-date research available?

  • Reorganized, revised and updated content and format—Text has been rewritten to reflect recent APA guidelines for the analysis and reporting of research.
    • Provides students with a streamlined presentation of the subject that will help them understand the difference between real science and pseudoscience. 
  • Repeated measures analyses material.
    • Provides students with more detailed information regarding comparisons on more than two conditions. 
  • Focused data analyses and associated effect sizes material added.
    • Familiarizes students with using the F table to find p. 
  • Computing and interpreting confidence intervals for proportions, means and effect sizes. 
    • Provides students with detailed information on computing and interpreting confidence intervals. 
  • Reliability and validity discussion. 
    • Provides students with an improved flow of material in measurement research. 
  • A focus on useful data-analytic procedures—e.g., the effect size correlation and the confidence interval around the effect; the method of standardizing the margins in chi-square tables; the isolation of interaction residuals; the detective-like probing of reported data for an unreported effect size; and the file-drawer method of assessing robustness of an overall p value in meta-analysis.
    • Provides students with useful statistical methods, processes that are not typically found in undergraduate methods texts.

Are your students engaged with their text?

 

Complete student pedagogy, including:

  • Each chapter begins with a set of preview questions, which then appear as section headings in the chapter. The introduction to each chapter states the purpose of the chapter and gives an overview of its content.
  • Box discussions highlight and enliven concepts with practical examples and illustrations.
  • Each chapter ends with a summary of the main themes, followed by a list of key terms pegged to particular pages in which those terms are set off in bold-faced print.
  • Each chapter concludes with a set of review questions intended to stimulate thought and discussion, with answers given at the end of the chapter.  
  • A glossary at the back of the book lists and defines all key terms (in boldface) as well as other terms (in italics) in the text and notes the primary chapter(s) where each of those terms is discussed.    

 

Chapter 1 - Understanding empirical reasoning, the scientific method, levels of empirical investigation, and the characteristics of good researchers.

 

Chapter 2 - Creating, shaping, and polishing the research idea, doing a search of the literature, and writing the research proposal.

 

Chapter 3 - Weighing and balancing ethical considerations, and preparing for an ethics review.

 

Chapter 4 - Knowing the range of observational methods available for watching and recording behavior in lab and field settings, using archival

data and outside observers or judges, and knowing the limitations of these methods.

 

Chapter 5 - Knowing how to collect data in which the participants describe their own behavior or state of mind, and having a sense of the limitations of self-report methods.

 

Chapter 6 - Assessing reliability and validity of measuring tools and the validity of research designs.

 

Chapter 7 - Knowing about design options for randomized experiments, the nature and limits of causal reasoning, and how certain artifacts are anticipated and addressed.

 

Chapter 8 - Understanding the nature and limits of causal reasoning in research that does not use random assignment, including nonequivalent groups designs, interrupted time-series designs, single-case experimental research, and longitudinal research.

 

Chapter 9 - Understanding the logic and the limitations of probability sampling in survey research and the rationale and limitations of using opportunity samples in experimental research, and knowing how nonresponse bias and volunteer bias may be addressed.

 

Chapter 10 - Using graphics, statistical summaries, and confidence intervals to give an overall picture of the results, and using z score transformations on raw data.

 

Chapter 11 - Correlating and interpreting relationships between variables based on raw scores, dummy-coded variables, or a combination of both.

 

Chapter 12 - Testing hypotheses, understanding the effect size, creating a confidence interval around effect size correlations, using the BESD when assessing practical importance, doing a power analysis, and consulting prep to estimate the likelihood of replication.

 

Chapter 13 - Using t and r or d to compare two independent groups, understanding what circumstances maximize t, using the paired-t for two correlated conditions, and knowing about assumptions of t.

 

Chapter 14 - Understanding how F and t are related, using F in designs with more than two conditions and using t and r to examine simple effects, understanding factorial ANOVA and how obtained interactions are interpreted from residuals, computing F and t contrasts and r-type effect sizes in focused comparisons on more than two conditions, and understanding focused analyses on repeated measures.

 

Chapter 15 - Analyzing and interpreting 2´2 and larger tables of independent counts by chi-square, computing phi (f) as an effect size index for 1-df c2, using Mosteller's standardization procedure to interpret larger chi-square tables.

 

Appendix A - Writing up the research findings and conclusions in the style of the APA publication manual and preparing a poster.

 

Appendix C - Comparing and combining r-type effect sizes in meta-analyses, obtaining overall significance levels, estimating the tolerance for future null results, and using the null-counternull interval as protection against Type II errors.

PREFACE

 

PART I     Getting Started

 

CHAPTER 1     Behavioral Research and the Scientific Method

Preview Questions

Why Study Research Methods and Data Analysis?

What Rival Alternatives Are There to the Scientific Method?

What Is Empirical Reasoning?

How Is Empirical Reasoning Used in Psychological Science?

How Do Extra-Empirical Factors Play a Role?

What Does Behavioral Science Encompass?

What Do Methodological Pluralism and Theoretical Ecumenism Connote?

How Does Research Go From Descriptive to Relational to Experimental?

What Are the Characteristics of Good Researchers?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 2     Creative Ideas and Working Hypotheses

Preview Questions

What Is the "Discovery Phase" of Scientific Inquiry?

What Are Hypothesis-Generating Heuristics?

What Belongs in My Research Proposal?

How Can I Do a Literature Search?

How Should I Go About Defining Variables?

What Identifies "Good" Theories and Working Hypotheses?

What Is Meant by Independent Variable and Dependent Variable?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 3     Ethical Considerations and Guidelines

Preview Questions

How Do Ethical Guidelines in Research Function?

What Is Informed Consent, and When Is It Used?

How Are Ethics Reviews Done and Acted Upon?

What Are Obstacles to the Rendering of "Full Justice"?

How Can a "Relationship of Trust" Be Established?

How Do Scientific Quality and Ethical Quality Intertwine?

Is Deception Ever Justified?

What Is the Purpose of Debriefing, and How Do I Do It?

How Is Animal Research Governed By Ethical Rules?

What Are My Ethical Responsibilities When Writing Up My Research?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

PART II     Observation and Measurement

 

CHAPTER 4     Strategies of Systematic Observational Research

Preview Questions

What Is Meant By Systematic Observational Research?

How Do Researchers Simultaneously Participate and Observe?
What Can Be Learned By Quantifying Observations?

How Is a Content Analysis Done?

How Are Raters or Coders Chosen For a Judgment Study?

How Are Situations Simulated in Experimental Research?

How Do I Identify Rival Interpretations and Rival Hypotheses?

What Is the Distinction Between Reactive and Nonreactive Observation?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 5     Methods for Looking Within Ourselves

Preview Questions

What Are Uses and Limitations of Self-Report Measures?

What Are Open-Ended and Fixed-Choice Items?

How Are Personality and Projective Tests Used?

What Are Numerical, Forced-Choice, and Graphic Ratings?

What Are Rating Errors, and How Do I Control Them?

What Are Semantic Differentials, Likert Scales, and Thurstone Scales?

How Do I Prepare Items For a Questionnaire or an Interview?

How Are Face-to-Face and Telephone Interviews Done?

How Are Behavioral Diaries Used in Research?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 6     Reliability and Validity in Measurement and Research

Preview Questions

What Is the Difference Between Validity and Reliability?

What Are Random and Systematic Errors?

What Is the Purpose of Retest and Alternate-Form Reliability?

What Is Internal-Consistency Reliability, and How Is It Increased?

What Is Acceptable Test-Retest and Internal-Consistency Reliability?

How Do I Measure the Reliability of Judges?

How Is Reliability Related To Replication and External Validity?

How Are Content and Criterion Validity Defined?

How Is Construct Validity Assessed in Test Development?

What Are Four Types of Validity in Experimental Design?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

PART III     Design and Implementation

 

CHAPTER 7     Randomized Experiments and Causal Inference

Preview Questions

What Is the Purpose of Doing Randomized Experiments?

How Is Random Assignment Accomplished?

What Are Between-Subjects and Within-Subjects Designs?

What Are Factorial Designs and Latin Square Designs?

Why Is Causality Said To Be "Shrouded in Mystery"?

On What Grounds Do Scientists Infer Causality?

What Is the Formative Logic of Experimental Control?

What Are "Preexperimental Designs"?

What Circumstances Jeopardize Internal Validity?

How Can I Control For Demand Characteristics and Expectancy Effects?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 8     Nonrandomized Research and Causal Reasoning

Preview Questions

How Is Causal Reasoning Attempted in the Absence of Randomization?

What Is the "Third Variable" Problem?

How Can Causal Effects Be Studied in Nonequivalent Groups?

What Are Time-Series Designs and "Found Experiments"?

What Within-Subjects Designs Are Used in Single-Case Experiments?

How Are Correlations Interpreted in Cross-Lagged Panel Designs?

What Is the Purpose of Longitudinal Research Using Cohorts?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 9     Survey Research and Subject Recruitment

Preview Questions

What Are Opportunity and Probability Samples?

What Is Meant By Bias and Instability in Survey Research?

Why Is "Bias" in Sampling Such an Elusive Concept?

How Can I Do Simple Random Sampling?

What Are Stratified Random Sampling and Area Probability Sampling?

What Did the Literary Digest Case Teach Pollsters?

What Are Point Estimates and Interval Estimates?

What Are the Benefits of Stratification?

How Is Nonresponse Bias Handled in Survey Research?

What Are Typical Characteristics of Volunteer Subjects?

How Is Volunteer Bias in Opportunity Samples Managed?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

PART IV     Describing Data and Making Inferences

 

CHAPTER 10     Summarizing the Data

Preview Questions

How Is Visual Integrity Ensured When Graphing Results?

How Are Frequencies Displayed in Tables, Bar Graphs, and Line Graphs?

How Do Stem-and-Leaf Charts Work?

How Are Percentiles Used to Summarize Part of a Batch?

How Might an Exploratory Data Analysis Be Done?

How Does Asymmetry Affect Measures of Central Tendency?

How Do I Measure How "Spread Out" a Set of Scores Is?

What Are Descriptive and Inferential Measures?

How Do I Compute a Confidence Interval Around a Population Mean?

What Is Distinctive About the Normal Distribution?

Why Are z Scores Called Standard Scores, and How Are They Used?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 11     Correlating Variables

Preview Questions

What Are Different Forms of Correlations?

How Are Correlations Visualized in Scatter Plots?

How Is the Product-Moment r Calculated?

How Is the Spearman Rank Correlation Computed?

How Is "Dummy Coding" Used in Correlation?

When is the Phi Coefficient Used?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 12     Statistical Significance, Effect Size, and Power Analysis

Preview Questions

Why Is It Important to Focus Not Just on p Values?

What is the Reasoning Behind Null Hypothesis Significance Testing?

What Do Type I and Type II Errors Imply in Practical Terms?

How Do I Determine, Interpret, and Report the Statistical Significance of r?

What Is the Purpose of the Binomial Effect-Size Display?

How Can I Do a Power Analysis?

How Do I Compute a Confidence Interval for an Effect Size r?

What Would Computing Killeen's prep tell me?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

PART V     Statistical Tests

 

CHAPTER 13     The Comparison of Two Conditions

Preview Questions

What Do "Signal-to-Noise" Ratios Have to Do With t Tests?

How Do I Compute an Independent Sample t Test?

What Can a Table of p Values for t Teach Me?

How Can I Estimate reffect size From an Independent Sample t?

How Can I Estimate Cohen's d From an Independent Sample t?

How Do I Interpret Cohen's d for Independent Groups?

How Can I Maximize the Independent Sample t?

How Does a Paired t Test Differ From an Independent Sample t Test?

What Are Statistical Assumptions of the t Test?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 14     Comparisons On More Than Two Conditions

Preview Questions

What Is Analysis of Variance (ANOVA), and How Are F and t Related?

How Is Variability Apportioned in a One-Way ANOVA?

How Are ANOVA Summary Tables Set Up and Interpreted?

How Can I Test for Simple Effects After an Omnibus F?

How Is Variability Apportioned in a Two-Way ANOVA?

How Do I Interpret Main and Interaction Effects?

How Is a Two-Way ANOVA Computed and a Summary Table Set Up?

How Do I Compute a Focused t or F On More Than Two Groups?

What Do reffect size, ralerting, and rcontrast tell us?

How Are Contrasts On Repeated Measures Computed?

How Are Latin Square Designs Analyzed by Contrasts?

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

CHAPTER 15     The Analysis of Frequency Tables

Preview Questions

What Is the Purpose of Chi-Square (c2)?

How Do I compute 1-df Chi-Squares?

How Do I Obtain the p Value, Effect Size, and Confidence Interval?

What Is the Relationship Between 1-df c2 and Phi?

How Do I Deal With Tables Larger Than 2 ´ 2?

How Does "Taking the Margins Into Account" Work?

A Journey Begun

Summary of Ideas

Key Terms

Multiple-Choice Questions for Review

Discussion Questions for Review

Answers to Review Questions

 

APPENDIX A     Communicating Your Research Findings

Research Reports and Poster Presentations

Getting Organized

Sample Research Report

Title Page

Abstract

Introduction

Method

Results

Discussion

References

End Material

Writing and Revising

Layout and Printing

Creating a Poster

 

APPENDIX B     Statistical Tables

B.1.  z Values and Their Associated One-Tailed p Values

B.2.  t Values and Their Associated One-Tailed and Two-Tailed p Values

B.3.  F Values and Their Associated p Values

B.4  c2 Values and Their Associated p Values

B.5.  r Values and Their Associated p Values

B.6.  Transformations of r to Fisher zr

B.7.  Transformations of Fisher zr to r

 

APPENDIX C     Introduction to Meta-Analysis

The Purpose of Meta-Analysis

Comparing Two Effect Sizes

Combining Two Effect Sizes

Obtaining an Overall Significance Level

Detective-Like Probing of Reported Data

The File Drawer Problem

The Counternull Statistic

 

GLOSSARY

REFERENCES

NAME INDEX

SUBJECT INDEX

For Research Methods / Experimental Methods


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