Robert Rosenthal is Distinguished Professor at the University of
California at Riverside and Edgar Pierce Professor of Psychology,
Emeritus, Harvard University. His research has centered for some 50
years on the role of the self-fulfi lling prophecy in everyday life
and in laboratory situations. Special interests include the effects
of teachers’ expectations on students’performance, the effects of
experimenters’expectations on the results of their research, and
the effects of clinicians’expectations on their patients’mental and
physical health. He also has strong interests in sources of
artifact in behavioral research and in various quantitative
procedures. In the realm of data analysis, his special interests
are in experimental design and analysis, contrast analysis, and
meta-analysis. His most recent books and articles are about these
areas of data analysis and about the nature of nonverbal
communication in teacher-student, doctorpatient, manager-employee,
judge-jury, and psychotherapist-client interaction. He has been
Co-Chair of the Task Force on Statistical Inference of the American
Psychological Association and has served as Chair of the Research
Committee of the Bayer Institute for Health Care Communication. He
was a co-recipient of two behavioral science awards of the American
Association for the Advancement of Science 1960,1993 and
recipient of the James McKeen Cattell Award of the American
Psychological Society, the Distinguished Scientist Award of the
Society of Experimental Social Psychology, the Samuel J. Messick
Distinguished Scientifi c Contributions Award of the APA’s Division
5—Evaluation, Measurement, and Statistics, and the APA’s
Distinguished Scientifi c Award for Applications of Psychology.
Ralph L. Rosnow is Thaddeus Bolton Professor Emeritus at Temple
University, where
he taught for 34 years and directed the graduate program in social
and organizational
psychology. He has also taught research methods at Boston
University and Harvard
University and does consulting on research and data analysis. The
overarching theme
of his scholarly work concerns how people make sense of, and impose
meaning on,
their experiential world, called the “will to meaning” by Viktor
Frankl. Rosnow has
explored aspects of this construct in research and theory within
the framework of
contextualism, the psychology of rumor and gossip, attitude and
social cognition, the
structure of interpersonal acumen, artifacts and ethical dilemmas
in human research,
and the statistical justifi cation of scientifi c conclusions. He
has authored and coauthored
many articles and books on these topics and, with Mimi Rosnow,
coauthored Writing
Papers in Psychology, a popular writing manual now in its seventh
edition published
by Thomson Wadsworth, 2006. He has served on the editorial boards
of journals and
encyclopedias, was coeditor with R. E. Lana of the Reconstruction
of Society Series
published by Oxford University Press, and chaired the APA’s
Committee on Standards
in Research. He is a fellow of the American Association for the
Advancement of
Science, the APA, and the Association for Psychological Science,
received the Society
of General Psychology’s George A. Miller Award, and was recently
honored with a
Festschrift book edited by D. A. Hantula, Advances in Social and
Organizational Psychology
Rosenthal and Rosnow have also collaborated on other books on
research methods
and data analysis, including Artifact in Behavioral Research
Academic Press, 1969;
The Volunteer Subject Wiley, 1975; Primer of Methods for the
Behavioral Sciences
Wiley, 1975; Understanding Behavioral Science: Research Methods
for Research
Consumers McGraw-Hill, 1984; Contrast Analysis: Focused
Comparisons in the
Analysis of Variance Cambridge University Press, 1985; People
Studying People:
Artifacts and Ethics in Behavioral Research W. H. Freeman, 1997;
with D. B. Rubin
Contrasts and Effect Sizes in Behavioral Research: A Correlational
Approach
Cambridge University Press, 2000; and Beginning Behavioral
Research: A Conceptual
Primer 6 th ed., PearsonPrenticeHall, 2008.
详细目录
PART I CONCEPTUAL AND ETHICAL FOUNDATIONS 1
Chapter 1 The Spirit of Behavioral Research 3
Science and the Search for Knowledge 3
What Do Behavioral Researchers Really Know? 6
Social Constructionism 7
ContextualismPerspectivism 9
Evolutionary Epistemology 12
Peirce’s Four Ways of Knowing 13
Rhetoric, Perceptibility, and Aesthetics 15
Limitations of the Four Supports of Conviction 18
Behavioral Research Defi ned 18
Three Broad Research Orientations 21
The Descriptive Research Orientation 23
The Relational Research Orientation 25
The Experimental Research Orientation 29
Empirical Principles as Probabilistic Assertions 32
Orienting Habits of Good Scientifi c Practice 34
Chapter 2 Contexts of Discovery and Justifi cation 37
Inspiration and Explanation 37
Theories and Hypotheses 38
Sources of Inspiration and Insight 39
Serendipity in Behavioral Research 42
Molding Ideas Into Working Hypotheses 43
Positivism, Falsifi cationism, and Conventionalism 48
Type I and Type II Decision Errors 53
Statistical Signifi cance and the Effect Size 55
Two Families of Effect Sizes 56
Interval Estimates Around Effect Sizes 58
Summing Up 59
Chapter 3 Ethical Considerations, Dilemmas,and Guidelines 61
Puzzles and Problems 61
A Delicate Balancing Act 63
Historical Context of the American Psychological Association Code
64
The Belmont Report, Federal Regulations, and the
Institutional
Review Board 67
Principle I: Respect for Persons and Their Autonomy 69
Principle II: Benefi cence and Nonmalefi cence 71
Principle III: Justice 74
Principle IV: Trust 76
Principle V: Fidelity and Scientifi c Integrity 77
Costs, Utilities, and Institutional Review Boards 79
Scientifi c and Societal Responsibilities 82
PART II OPERATIONALIZATION AND MEASUREMENT OF DEPENDENT VARIABLES
85
Chapter 4 Reliability and Validity of Measurements 87
Random and Systematic Error 87
Assessing Stability and Equivalence 89
Internal-Consistency Reliability and Spearman-Brown 92
KR20 and Cronbach’s Alpha 94
Effective Reliability of Judges 98
Effective Cost of Judges 100
Effective Cost of Items 102
Interrater Agreement and Reliability 103
Cohen’s Kappa 105
Replication in Research 111
Validity Criteria in Assessment 113
Convergent and Discriminant Validity 115
Test Validity, Practical Utility, and the Taylor-Russell Tables
117
Relationship of Validity to Reliability 119
Chapter 5 Observations, Judgments, and Composite Variables
123
Observing, Classifying, and Evaluating 123
Observing While Participating 124
Maximizing Credibility and Serendipity 125
Organizing and Sense-Making in Ethnographic Research 127
Interpreter and Observer Biases 128
Unobtrusive Observations and Nonreactive Measurements 130
Selecting the Most Appropriate Judges 134
Choosing the Number of Response Alternatives 137
Effects of Guessing and Omissions on Accuracy 138
Intrinsic Factors and the Level of Accuracy 140
Applications of Categorical Judgments 141
Category Scales and Rating Scales 145
Numerical, Graphic, and Magnitude Ratings 146
Rating Biases and Their Control 150
Bipolar Versus Unipolar Scales 151
Forming Composite Variables 151
Forming Multiple Composites 154
Quantifying the Clarity of Composites 156
Chapter 6 Questionnaires, Interviews, and Diaries 160
Concerns About Self-Report Data 160
Open-Ended Versus Structured Items 163
Critical Incident Technique 165
Stages in Developing Interview Protocols 167
Research Interviews by Telephone 171
Developing Research Questionnaires 172
Defensiveness, Inconsistency, and Yea-Saying 174
Cross-Cultural Questionnaire and Interview Research 176
One-Dimensional and Multidimensional Attitude Scales 177
Semantic Differentials for Attitudinal Meaning 178
Q-Sorts for Subjectivity Ratings 179
Likert Method of Item Analysis 181
Thurstone Equal-Appearing Intervals Method 182
Memory and the Use of Self-Recorded Diaries 185
PART III THE LOGIC OF RESEARCH DESIGNS 187
Chapter 7 Randomized Controlled Experiments and Causal Inference
189
Experimentation in Science 189
Randomized Experimental Designs 190
Characteristics of Randomization 193
The Philosophical Puzzle of Causality 196
Contiguity, Priority, and Constant Conjunction 198
Four Types of Experimental Control 200
Mill’s Methods of Agreement and Difference 201
Between-Group Designs and Mill’s Joint Method 203
Independent, Dependent, and Moderator Variables 204
Solomon’s Extended Control Group Design 206
Threats to Internal Validity 209
Threats to External Validity 212
Statistical Conclusion and Construct Validity 215
Subject and Experimenter Artifacts 216
Demand Characteristics and Their Control 220
Interactional Experimenter Effects 223
Experimenter Expectancy Effects and
Their Control 226
Concluding Commentary 230
Chapter 8 Nonrandomized Research and Functional Relationships
233
Nonrandomized and Quasi-Experimental Studies 233
Nonequivalent Groups and Historical Controls 235
Interrupted Time Series and the Autoregressive Integrated Moving
Average 238
Single-Case Experimental Designs 239
Cross-Lagged Correlational Designs 242
Invisible Variables and the Mediation Problem 245
Path Analysis and Causal Inference 246
The Cohort in Longitudinal Research 250
Different Forms of Cohort Studies 252
Subclassifi cation on Propensity Scores 256
Multiple Confounding Covariates 257
Chapter 9 Randomly and Nonrandomly Selected Sampling Units
260
Sampling a Small Part of the Whole 260
Bias and Instability in Surveys 262
Simple Random-Sampling Plans 264
Improving Accuracy in Random Sampling 266
Confi dence Intervals for Population Estimates 269
Speaking of Confi dence Intervals 270
Other Selection Procedures 271
Nonresponse Bias and Its Control 273
Studying the Volunteer Subject 276
Characteristics of the Volunteer Subject 278
Implications for the Interpretation of
Research Findings 284
Situational Correlates and the Reduction of
Volunteer Bias 285
The Problem of Missing Data 288
Procedures for Dealing With Missing Data 289
PART IV FUNDAMENTALS OF DATA ANALYSIS 291
Chapter 10 Describing, Displaying, and Exploring Data 293
Descriptions of Sampling Units 293
Frequency Diagrams and Stem-and-Leaf Displays 294
Box Plots 297
Comparing Distributions Back to Back 298
Measures of Central Tendency 299
Measures of Spread 300
The Normal Distribution 304
Standard Scores 305
Data Not Distributed Normally 306
Precision of Estimating Population Means 307
Defi ning Outliers 309
Coping With Outliers 310
Exploring the Data 311
Chapter 11 Correlation 314
Pearson r 314
Proportion of Variance Interpretation of Correlation 316
Binomial Effect-Size Display 318
Confi dence Intervals for Effect-Size Correlations 322
Small Correlations, But Important Effects 324
Counternull Values of Effect Sizes 328
Spearman Rank Correlation 330
Ranks as a Transformation 332
Observations of Disproportionate Infl uence 333
Point-Biserial Correlation 336
Exact Tests for Rho 339
Phi Coeffi cient 340
Curvilinear Quadratic Correlation 344
Five Product-Moment Correlations 346
Comparing Correlations 347
Considering Third Variables 347
Effects of Variability on Correlations 349
Chapter 12 Statistical Power and Effect Size Revisited 354
Why Assess Statistical Power? 354
The Neglect of Statistical Power 357
The requivalent Statistic 359
Cohen’s Multipurpose Power Tables 360
The t Test for Comparing Two Means 363
The Signifi cance of a Product-Moment r 366
Differences Between Correlation Coeffi cients 369
The Test That a Proportion is .50 373
The Difference Between Proportions 373
The Focused Chi-Square Test 374
F Tests for Focused Comparisons 375
Additional Strategies for Improving Power 376
PART V ONE-WAY DESIGNS 379
Chapter 13 Comparing Means by Standard t Tests 381
Gosset and the t Test 381
Two Components of t Tests 382
Maximizing t 383
Effect Sizes and Adjustments for Unequal Sample Sizes 385
Interpreting the Independent Sample t 388
Computing the Independent Sample t 391
Reporting the Results 392
t Tests for Nonindependent Samples 395
Effect Size and Study Size Components of Nonindependent Sample t
397
Assumptions Underlying t Tests 401
Nonparametric Procedures 403
The Bootstrap, the Jackknife, and Permutation Tests 405
Chapter 14 Analysis of Variance and the F Test 409
The F Test and the t Test 409
The Analysis of “Variances” 410
Illustration of an Omnibus F 412
Dividing Up the Total Variance 413
ANOVA Summary Tables 414
Distributions of F 417
After the Omnibus F 418
Protecting Against “Too Many t Tests” 421
Bonferroni Procedures 422
Bonferroni Tolerance Value 425
Comparing Two Independent Variabilities 425
Illustration Using Transformations 426
Comparing Two Correlated Variabilities 429
Comparing Three or More Independent Variabilities 431
Comparing Three or More Correlated Variabilities 433
Summary of Procedures for Comparing Variabilities 433
Chapter 15 One-Way Contrast Analyses 434
Focusing Our Questions and Statistical Tests 434
Contrast F Tests on Original Data 436
Contrast t Tests on Original Data 440 Ca
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