designing experiments - semantic scholar€¦ · expected values and their applications....

DESIGNING EXPERIMENTSAND ANALYZING DATAA Model Comparison Perspective, Second EditionScott E. MaxwellUniversity of Notre DameHarold D. DelaneyUniversity of New Mexico

Through this book’s unique model comparison approach, students are introduced toa set of fundamental principles for analyzing data. After seeing how these principlescan be applied in simple designs, students are shown how these same principles alsoapply in more complicated designs. This establishes an integrative theme that showshow statistical methods appropriate for various experimental designs relate to oneanother. Drs. Maxwell and Delaney believe that the model comparison approach takesthe mystery out of analyzing data by:� better preparing students to understand the logic behind a general strategy of

data analysis appropriate for various designs; and� building a stronger foundation, which allows for the introduction of more complex topics omitted from

other books, such as the multivariate approach to repeated measures designs.

Several learning tools further strengthen the reader’s understanding:� Flowcharts assist in choosing the most appropriate technique for analyzing data.� An equation crossreferencing system aids in locating the initial, more detailed definition and numerous

summary equation tables assist readers in understanding similarities and differences between differentmethods for analyzing their data.

� Many examples based on actual research in a variety of behavioral sciences help students see theapplications of the material.

� Numerous exercises help develop a deeper understanding of the subject, through conceptual questionsand through focused analysis of small data sets. Numerous detailed solutions are provided at the backof the book.

� Realistic data sets allow the reader to see an analysis of data from each design in its entirety.

Updated throughout, the second edition features:� significantly increased attention to measures of effects, including confidence intervals, strength of

association, and effect size estimation for complex, as well as simple designs;� an increased use of statistical packages and the graphical presentation of data;� new chapters on multilevel models, including those for within-subject designs (Ch. 15) and hierarchical

designs (Ch. 16);� the current controversies regarding statistical reasoning, such as the latest debates on hypothesis

testing (Ch. 2);� a new preview of the experimental designs covered in the book (Ch. 2);� a new appendix describing how the general linear model integrates ANOVA and regression (Appendix

B, Part 1);� a new appendix presenting general principles of formulating statistical models (Appendix B, Part 2);� a CD with SPSS and SAS data sets for many of the text exercises, as well as tutorials reviewing basic

statistics and simple and multiple regression; and� a Web site containing up-to-the minute examples of SPSS and SAS syntax for analyzing many of the

text exercises.

Appropriate for advanced courses on experimental design or analysis, applied statistics, or analysis of variancetaught in departments of psychology, education, statistics, business, and other social sciences, the book isalso ideal for practicing researchers in these disciplines. A prerequisite of undergraduate statistics is assumed.An Instructor’s Solutions Manual is available to those who adopt the book for classroom use.

Contents: Preface. Part I: Conceptual Bases of Experimental Design and Analysis. The Logic of Experimental Design. Introduc-tion to the Fisher Tradition. Part II: Model Comparisons for Between-Subjects Designs. Introduction to Model Comparisons: One-Way Between-Subjects Designs. Individual Comparisons of Means. Testing Several Contrasts: The Multiple-ComparisonsProblem. Trend Analysis. Two-Way Between-Subjects Factorial Designs. Higher-Order Between-Subjects Factorial Designs.Designs With Covariates: ANCOVA and Blocking. Designs With Random or Nested Factors. Part III: Model Comparisons forDesigns Involving Within-Subjects Factors. One-Way Within-Subjects Designs: Univariate Approach. Higher-Order DesignsWith Within-Subjects Factors: Univariate Approach. One-Way Within-Subjects Designs: Multivariate Approach. Higher-Order Designs With Within-Subjects Factors: Multivariate Approach. Part IV: Alternative Analysis Strategies. An Introductionto Multilevel Models for Within-Subjects Designs. An Introduction to Multilevel Hierarchical Mixed Models: Nested De-signs. Appendices: Statistical Tables. Review of Basic Strategies. Linear Models; The Relation Between ANOVA and Regres-sion. Brief Primer of Principles of Formulating and Comparing Models. Notes. Solutions to Selected Exercises. References.0-8058-3718-3 [cloth with CD] / May 2003 / approx. 1104pp. / $99.950-8058-4675-1 [Instructor’s Solution Manual] / May 2003 / Free Upon Adoption

New Edition

Research Methods/Experimental Design

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UNDERSTANDING RESEARCHIN CLINICAL ANDCOUNSELING PSYCHOLOGY T

Edited by

Jay C. Thomas, Michel HersenPacific University

Understanding Research in Clinical and Counseling Psychology is a unique text because itis designed and written for the graduate students aspiring to careers in practice ratherthan in psychological science who are the vast majority in clinical and counselingprograms.

To motivate readers to see the value of knowledge produced by research, the bookopens with an actual case report that shows how research-generated strategiesincorporated into treatment allowed a woman who formerly would have beenconsidered so hopelessly incapacitated by obsessive-compulsive disorder as to requirelifetime institutionalization if not neurosurgery to return to normal family and work life.

The first set of chapters introduces fundamental concepts of measurement, sampling, and validity. The nextset systematically presents the kinds of investigations most relevant to budding practitioners—groupcomparisons, correlations, single-subject designs, program evaluations, and meta-analyses. Each of thesechapters concludes with a detailed example of a study in which students can see how the techniques describedare actually employed. The third set addresses enduring concerns—how to define and maintain ethicalstandards, how to do effective literature reviews and assess the quality of existing data, and how to collectand analyze data. It also addresses concerns that have emerged recently—how to distinguish and judgeeffective and efficacious treatments and how to contribute to research efforts as a private practitioner.

The issues involved in the often confusing effectiveness versus efficacy debate are illuminated with a clinicallyrelevant case example. Descriptions of alternatives to conventional significance testing, such as “clinicalsignificance” and “reliable change analyses” help students consider new ways in which they can imposerigor on their own research and practice activities. Two final chapters examine the challenges of studyingtwo special groups: children and older adults. Throughout, the authors, all capable researchers who are alsoexperienced practitioners, demonstrate the ways in which research is an essential foundation for effectiveand ethical practice. Students and instructors alike will welcome this reader-friendly book.

Contents: Preface. Part I: Research Foundations. J.C. Thomas, J. Rosqvist, Introduction: Science in the Service of Practice.W.W. Tryon, D. Bernstein, Understanding Measurement. K.A. Minke, S.N. Haynes, Sampling Issues. J.R. Scotti, T.L. Mor-ris, S.H. Cohen, Validity: Making Inferences From Research Outcomes. Part II: Research Strategies. J.T. Ehrenreich, A.M.Gross, Group Designs. G. Goldstein, Correlational Methods. K.A. Freeman, Single Subject Designs. M.M. Greene, ProgramEvaluation. J.A. Durlak, I. Meerson, C.J.E. Foster, Meta-Analysis. Part III: Research Practice. C. Miller, Ethical Guidelines inResearch. M.J. Gray, R. Acierno, Reviewing the Literature and Evaluating Existing Data. J.C. Thomas, L. Selthon, PlanningData Collection and Performing Analyses. Part IV: Special Problems. P. Truax, J.C. Thomas, Effectiveness Versus Efficacy Stu-dies. R. Warren, J.C. Thomas, Research in Private Practice. M.D. Rapport, R. Randall, G.N. Shore, K-M. Chung, ResearchWith Children. R. O’Hara, A.B. Higgins, J.A. D’Andrea, Q. Kennedy, D. Gallagher-Thompson, Research With Older Adults.0-8058-3671-3 [paper] / 2003 / 488pp. / $49.95

New EditionResearch Methods/Experimental Design

Research Methods/Experimental Design........................................... Inside FrontIntroductory Statistics ........................................................................................... 5Intermediate/Advanced Statistics and Methods ................................................... 6Computer Applications ....................................................................................... 12Teaching Resources ............................................................................................ 16For Course Adoption Consideration Only ......................................................... 20Order Form ......................................................................................................... 21

T denotes complimentary copies available—See page 20 for details


RESEARCH DESIGN ANDSTATISTICAL ANALYSIS TSecond EditionJerome L. Myers, Arnold D. WellUniversity of Massachusetts Amherst

Intended both as a textbook for students and as a resource for researchers, this bookemphasizes the statistical concepts and assumptions necessary to describe and makeinferences about real data. Throughout the book the authors encourage the reader toplot and examine their data, find confidence intervals, use power analyses to determinesample size, and calculate effect sizes. The goal is to ensure the reader understands:the underlying logic and assumptions of the analysis and what it tells them, thelimitations of the analysis, and the possible consequences of violating assumptions.

Using an intuitive, informal style, the authors adopt a “bottom-up” approach—asimpler, less abstract discussion of analysis of variance is presented prior to developingthe more general model. A concern for alternatives to standard analyses allows for the

integration of non-parametric techniques into relevant design chapters, rather than in a single, isolated chapter.This organization allows for the comparison of the pros and cons of alternative procedures within the researchcontext to which they apply.

Basic concepts, such as sampling distributions, expected mean squares, design efficiency and statistical modelsare emphasized throughout. This approach provides a stronger conceptual foundation in order to help thereader generalize the concepts to new situations they will encounter in their research and to better understandthe advice of statistical consultants and the content of articles using statistical methodology.

The second edition features a greater emphasis on:� Graphics—Two early chapters are now largely devoted to examples and discussion of displays of data

and there are more graphs throughout.� Confidence Intervals—Now are usually presented before hypothesis tests to help focus on the question

“what is the size of the effect” rather than “is there an effect.”� Measures of Effect Size—Now are introduced earlier, in the context of the t test, and then are routinely

discussed in a variety of research designs and analyses.� Power Analysis—Computer programs are now used to illustrate the calculation of power.� Tests of Contrasts—Now are introduced earlier (ch. 6) as extensions of the usual two-sample t

tests in order to simplify the discussion.� Elementary Probability—A new chapter on basic probability serves as a review and a means for

using the binomial distribution to introduce hypothesis testing.� Correlation and Regression—Now introduced earlier (ch. 3) and with an increased emphasis on

the most frequent misinterpretations made when using these analyses.� Real Data Sets—A free CD contains several real and artificial data sets used in the book in SPSS,

SYSTAT, and ASCII formats.

An Instructor’s Solutions Manual, containing the intermediate steps to all of the text exercises, is availablefree to adopters.

Contents: Preface. Introduction. Looking at Data: Univariate Distributions. Looking at Data: Relations Between QuantitativeVariables. Probability and the Binomial Distribution. Estimation and Hypothesis Tests: The Normal Distribution. Estima-tion, Hypothesis Tests, and Effect Size: The t Distribution. The Chi Square and F Distributions. Between Subjects Designs:One Factor. Contrasts Among Means. Trend Analysis. Multi-Factor Between-Subjects Designs: Significance Tests in the 2-Way Case. Multi-Factor Between-Subjects Designs: Further Developments. Repeated-Measures Designs. Mixed Designs:Between-Subjects and Within-Subjects Factors. Using Concomitant Variables to Increase Power: Blocking and Analysis ofCovariance. Hierarchical Designs. Latin Squares and Related Designs. More About Correlation. More About Bivariate Re-gression. Multiple Regression. Regression With Categorical and Quantitative Variables: The General Linear Model. Appen-dices: Notation and Summation Operations. Expected Values and Their Applications. Statistical Tables.0-8058-4037-0 [cloth with CD] / 2003 / 784pp. / $79.95Special Discount Price! $49.95Applies if payment accompanies order or for course adoption orders of 5 or more copies.No further discounts apply.0-8058-4438-4 [Instructor’s Manual] / 2003 / 120pp. / Free Upon Adoption

New Edition




PRINCIPLES AND METHODSOF SOCIAL RESEARCH TSecond EditionWilliam D. CranoClaremont Graduate UniversityMarilynn B. BrewerOhio State University

“It is an excellent source of information about social research issues. I have often used it as ahandy source of information and I have repeatedly recommended it to my undergraduate andgraduate research assistants. Many of them still consider the book their ‘methods bible.’ Thebook is remarkable in both the scope of methodological issues and in thoroughness and balancewith which they are examined.”

—Dr. Radmila PrislinSan Diego State University

An extensive revision, this classic text presents the most recent advances in social research design andmethodology. Drs. Crano and Brewer thoroughly describe the research process using methods derived frombasic principles of scientific inquiry and demonstrate how they apply to the study of human thought, affect,and behavior. These applications make it an indispensable resource for all fields of human social research,particularly communication, psychology, public health, and marketing. With a heavy emphasis on reliabilityand validity, the book considers experimental, quasi-experimental, and survey research designs in light ofthese qualities.

Principles and Methods of Social Research is noted for its:� emphasis on understanding the principles that govern the use of a method to facilitate the

researcher’s choice of the proper methodological approach;� use of the laboratory experiment as a point of reference for describing and evaluating field

experiments, correlational designs, quasi-experiments, and survey designs; and� unique chapter on the ethics of social research which emphasizes the social responsibility of

the researcher and the power a researcher wields, and provides tips on how to use it responsibly.

Highlights of the thoroughly expanded and updated edition include:� a new chapter on meta-analysis that demonstrates how to synthesize results across many studies;� a new chapter on social cognition methods that reviews judgment and choice measures, reaction time,

memory, and priming paradigms to help measure implicit thoughts and feelings;� the latest on experimental operations and procedures, such as implicit measures, simulations, and

Internet experiments;� expanded coverage of conducting experiments outside of the lab, including conducting experiments

on the Web;� more information on applied evaluation research methods, including efficacy and effectiveness research,

treatment of regression artifacts in field settings, comparison and interrupted time series designs, andregression-discontinuity designs;

� the latest cognitive research on questionnaire responses to shed light on how to improve test designand construction; and

� new sections on solving problems of reactivity, computer-assisted interviews, and assessing groupprocesses.

Intended as a text for upper-level and graduate courses in research methods in social psychology, the socialsciences, communications, and public health research. No previous methods courses are required.

Contents: Preface. Part I: Introduction to Social Research Methods. Basic Concepts. Fitting Research Design to Research Pur-pose: Internal and External Validity. Measuring Concepts: Reliability and Validity. Part II: Research Design Strategies. Design-ing Experiments: Variations on the Basics. Constructing Laboratory Experiments. External Validity of Laboratory Experi-ments. Conducting Experiments Outside the Laboratory. Correlational Design and Causal Analysis. Quasi-Experiments andEvaluation Research. Survey Design and Sampling. Part III: Data Collection Methods. Systematic Observational Methods andNaturalistic Research. Interviewing. Content Analysis. Scaling Stimuli: Social Psychophysics. Scaling Individuals: Question-naire Design and Rating Scale Construction. Social Cognition Methods: Measuring Implicit Thoughts and Feelings. Methodsfor Assessing Dyads and Groups. Part IV: Concluding Perspectives. Synthesizing Research Results: Meta-Analysis. SocialResponsibility and Ethics in Social Research.0-8058-3903-8 [cloth] / 2002 / 424pp. / $99.950-8058-3904-6 [paper] / 2002 / 424pp. / $43.95

New EditionResearch Methods/Experimental Design


EMPIRICAL DIRECTION IN DESIGN AND ANALYSIS T

Norman H. AndersonUniversity of California at San DiegoA Volume in the Scientific Psychology Textbook Series

“...Anderson’s latest book is truly remarkable. It is a graduate level text with the first 12 chapters covering core principlesand the remaining 9 chapters serving as an excellent reference on numerous statistical methods and design issues....Thebook captivates your attention as topics are addressed from a perspective you’ve never entertained when studying statisticsand experimental design.”

—Air Force Research Laboratory–Science and Technology

The goal of Norman H. Anderson’s book is to help students develop skills of scientific inference. To accomplishthis he organized the book around the “Experimental Pyramid”—six levels that represent a hierarchy ofconsiderations in empirical investigation—conceptual framework, phenomena, behavior, measurement,design, and statistical inference. To facilitate conceptual and empirical understanding, Anderson de-emphasizes computational formulas and null hypothesis testing.

Other unique features include:� emphasis on visual inspection as a basic skill in experimental analysis to help students develop an

intuitive appreciation of data patterns;� exercises that emphasize development of conceptual and empirical application of methods of design

and analysis and de-emphasize formulas and calculations; and� heavier emphasis on confidence intervals than significance tests.

The book is intended for use in graduate-level experimental design/research methods or statistics courses inpsychology, education, and other applied social sciences, as well as a professional resource for activeresearchers. The first 12 chapters present the core concepts graduate students must understand. The nextnine chapters serve as a reference handbook by focusing on specialized topics with a minimum of technicalities.

Contents: Scientific Inference. Statistical Inference. Elements of ANOVA-I. Elements of ANOVA-II. Factorial Design. Re-peated Measures Design. Understanding Interactions. Confounding. Regression and Correlation. Frequency Data and Chi-Square. Single Subject Design. Nonnormal Data and Unequal Variance. Analysis of Covariance. Design Topics I. DesignTopics II. Multiple Regression. Multiple Comparisons. Sundry Topics. Foundations of Statistics. Math Models for ProcessAnalysis. Toward Unified Theory. Principles & Tactics for Writing. Lifelong Learning. Basic Statistical Concepts.0-8058-3978-X [cloth] / 2001 / 880pp. / $65.000-8058-4083-4 [Instructor’s Manual] / 2001 / 96pp. / Free Upon Adoption

See AlsoComputer Applications, pages 12–15



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STATISTICS IN PLAIN ENGLISH TTimothy C. UrdanSanta Clara University

“Overall, valuable to those who have great difficulty in understanding everyday language usingstatistical terminology and concepts.”

—CHOICE

“This compact softbound book delivers the promise implied by the title....Many undergraduateswho feel they are suffering from being forced to endure a statistics class will find this book quitereadable and helpful....The next time m yfather-in-law asks me a question about basic statistics,I may have to send him this book....The writing style is narrative and not intimidating....Finally,teachers of statistics may find the intuitive discussions in the book helpful for crafting lectures.”

—American Statistician

This book’s goal is to present statistical concepts and techniques in simple, everydaylanguage. It provides short, simple descriptions and explanations of a number ofstatistics or concepts. Each chapter is a self-contained unit comprised of three sections. Section 1 provides abrief description of the statistic, including how it is used and what information it provides. Section 2 reviewshow it works, how to calculate the formula, the strengths and weaknesses of the technique, and the conditionsneeded for its use. Section 3 concludes with an example that uses and interprets the statistic. A glossary ofterms and symbols is also included.

This brief paperback is an ideal supplement for statistics, research methods, or any course that uses statistics,or as a handy reference tool to refresh one’s memory about key concepts. The actual research examples arefrom a variety of fields, including psychology and education.

Contents: Preface. Measures of Central Tendency. Measures of Variability. The Normal Distribution. Standardization and zScores. Standard Errors. Statistical Significance and Effect Size. Correlation. t Tests. One-Way Analysis of Variance. FactorialAnalysis of Variance. Repeated-Measures Analysis of Variance. Regression. Appendices: Area Under the Normal CurveBetween µ and z and Beyond z. The t Distribution. The F Distribution. Critical Values of the Studentized Range Statistic (forthe Tukey HSD Test).0-8058-3442-7 [paper] / 2001 / 160pp. / $19.95

AN INTRODUCTION TO STATISTICAL CONCEPTSFOR EDUCATION AND BEHAVIORAL SCIENCES TRichard G. LomaxUniversity of Alabama

“Lomax...uses a straightforward, streamlined approach to teaching this often-hated subject. His user-friendly book includescoverage of many of the important topics in descriptive as well as inferential statistics....Recommended.”

—CHOICE

This book provides comprehensive coverage so that it can be used in a single- or two-course sequence instatistics. It provides greater flexibility because it contains many topics not dealt with in other introductorytexts. Its conceptual, intuitive approach allows for concepts to be easily stated and related to real-life examples.Throughout the text the author demonstrates how many statistical concepts can be related to one another.

Contents: Preface. Introduction. Data Representation. Univariate Population Parameters and Sample Statistics. The NormalDistribution and Standard Scores. Introduction to Probability and Sample Statistics. Introduction to Hypothesis Testing:Inferences About a Single Mean. Inferences About the Difference Between Two Means. Inferences About Proportions. Infer-ences About Variances. Bivariate Measures of Association. Simple Linear Regression. Multiple Regression. One-Factor Analysisof Variance—Fixed-Effects Model. Multiple-Comparison Procedures. Factorial Analysis of Variance—Fixed-Effects Model.Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Models. Hierarchical and Randomized Block Analysis of Variance Models.0-8058-2749-8 [cloth] / 2001 / 528pp. / $69.950-8058-3737-X [Instructor’s Manual] / 2001 / 74pp. / Free Upon Adoption

See AlsoLomax/Statistical Concepts: A Second Course for Education

and the Behavioral Sciences, Second Edition, page 9

Introductory Statistics



New EditionSTATISTICAL POWER ANALYSISA Simple and General Model for Traditional andModern Hypothesis Tests, Second EditionKevin R. MurphyPennsylvania State UniversityBrett MyorsGriffith University

“It is a terrific supplemental text for my class and I refer graduate students to it as they preparetheir dissertation proposals....They turn to it for their research, and that is a very good sign.”

—Dr. James W. LichtenbergUniversity of Kansas

This authored book presents a simple and general method for conducting statisticalpower analysis based on the widely used F statistic. The book illustrates how these

analyses work and how they can be applied to problems of studying design, to evaluate others’ research, andto choose the appropriate criterion for defining “statistically significant” outcomes. The book examines thefour major applications of power analysis, concentrating on how to determine:� the sample size needed to achieve desired levels of power;� the level of power that is needed in a study;� the size of effect that can be reliably detected by a study; and� sensible criteria for statistical significance.

Highlights of the second edition include:� a CD with an easy-to-use statistical power analysis program;� a new chapter on power analysis in multi-factor ANOVA, including repeated measures designs; and� a new One-Stop PV Table to serve as a quick reference guide.

The previous edition was the first book to discuss in detail the application of power analysis to both traditionalnull hypothesis tests and to minimum-effect testing. This book demonstrates how the same basic modelapplies to both types of testing. Drawing from the behavioral and social sciences, the authors present thematerial in a nontechnical way so that readers with little expertise in statistical analysis can quickly obtainthe values needed to carry out the power analysis for a range of hypotheses.

Contents: Preface. The Power of Statistical Tests. A Simple and General Model for Power Analysis. Using Power Analysis.Multi-Factor ANOVA and Repeated-Measures Studies. Illustrative Examples. Implications of Power Analysis. Appendices:Working with the Noncentral F Distribution. One-Stop F Table. One-Stop PV Table. dferr Needed for Power=.80 (α=.05) inTests of Traditional Null Hypothesis. dferr Needed for Power=.80 (α=.05) in Tests of Hypothesis That Treatments Account for1% or Less of the Variance in Outcomes.0-8058-4525-9 [cloth with CD] / May 2003 / approx. 184pp. / $45.000-8058-4526-7 [paper with CD] / May 2003 / approx. 184pp. / $22.50

APPLIED MULTIPLE REGRESSION/CORRELATION ANALYSIS FORTHE BEHAVIORAL SCIENCESThird EditionJacob CohenNew York UniversityPatricia CohenNew York State Psychiatric Institute and Columbia UniversityStephen G. West, Leona S. AikenArizona State University

“I can’t see how a practicing research psychologist could be without a copy.”—Dr. Steven P. Reise

University of California at Los Angeles

New Edition

Intermediate/Advanced Statistics and Methods New Edition


“I think VERY highly of this revision....The chapter on regression diagnostics and graphics (Ch. 4) is a wonderfuladdition. Also, the emphasis on confidence intervals is great, as is the extensive discussion on logistic regression.”

—Dr. William F. ChaplinUniversity of Alabama, Tuscaloosa

Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences is the classic text on multiple regression.It is noted for its non-mathematical, applied, and data-analytic approach intended to teach the reader “howto do it.” Students and researchers profit from its verbal-conceptual exposition and frequent use of concreteexamples. The applied emphasis provides clear illustrations of the principles and provides worked examplesof the types of applications that are possible. Researchers learn how to specify regression models that directlyaddress their research questions of interest. Early in the text an overview of the fundamental ideas of multipleregression and a review of bivariate correlation and regression and other elementary statistical conceptsprovide a strong foundation for a solid understanding of the rest of the text.

The third edition reflects state-of-the-art practices in the field:� An increased emphasis on graphics provides greater understanding of data.� An increased emphasis on the use of confidence intervals and effect size measures provides moreinformation about the size and precision of relationships.� An accompanying CD contains data for most of the numerical examples along with the computer codefor SPSS, SAS, and SYSTAT. These computer scripts can serve as templates for the analysis of the student’sown data.� Five entirely new chapters are included: Assumptions of the regression model and remedies whenthey are not met (Ch. 4), detection and treatment of the potential problems of outliers and multicollinearity(Ch. 10), alternative regression models that may be used when the dependent variable is binary, orderedcategory, or count in form, including logistic, ordinal logistic, Poisson regression, and the generalized linearmodel (Ch. 13), multilevel models for data collected in groups or other clusters (Ch. 14), and the analysis oflongitudinal data (Ch. 15).� Extensively revised chapters on curvilinear relationships and transformations (Ch. 6), interactionsbetween continuous variables (Ch. 7), interactions between categorical and continuous variables (Ch. 9), andmissing data (Ch. 11) reflect the latest developments in these areas.� Clear coverage of classic issues in regression and correlation with one or more continuous or categoricalpredictors is provided.� A new end-of-text glossary provides definitions of key terms.� A new appendix featuring statistical symbols, abbreviations, tests, and functions serves as a handyreference tool.

Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences serves as both a textbook for graduatestudents and as a reference tool for researchers in the basic and applied behavioral sciences, includingpsychology, education, health sciences, communications, business, sociology, political science, anthropology,and economics. Only an introductory knowledge of statistics is required. Largely self-standing chaptersminimize the need for researchers to refer to previous chapters. The book is an ideal text for courses on basicand advanced topics in multiple regression and correlational methods.

Contents: Preface. Introduction. Bivariate Correlation and Regression. MRC With Two or More Independent Variables. DataVisualization, Exploration, and Assumption Checking: Diagnosing and Solving Regression Problems I. Data Analytic Strat-egies Using MRC. Quantitative Scales, Curvilinear Relationships, and Transformations. Interactions Among ContinuousVariables. Categorical or Nominal Scales as Independent Variables. Interactions Involving Categorical Variables. Outliersand Multicollinearity: Diagnosing and Solving Regression Problems II. Coping With Missing Data. MRC and Causal Mod-els. Alternative Regression Models: Logistic, Poisson Regression, and the Generalized Linear Model. Random CoefficientRegression and Multilevel Models. Longitudinal Regression Methods. Multiple Dependent Variables: Set Correlation andCanonical Correlation.0-8058-2223-2 [cloth] / 2003 / 728pp. / $65.00

Intermediate/Advanced Statistics and Methods

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APPLIED MULTIVARIATE STATISTICSFOR THE SOCIAL SCIENCESFourth EditionJames P. StevensUniversity of Cincinnati

“My students...speak highly of the presentation of the material in the Stevens text. They findthe topics explained in a clear, concise fashion. They also like the examples and the computerprintout explanations.”

—Dr. Douglas A. PenfieldRutgers, The State University of New Jersey

“...Dr. Stevens writes so clearly. My students tell me in unsolicited comments that his text ishelpful in developing their understanding. The material is presented in an informative andengaging manner.”

—Dr. Gary J. LautenschlagerUniversity of Georgia

“The liberal inclusion of data examples using such packages as SAS and SPSS is especially helpful to the students.”—Dr. Daniel D. Blaine

University of Hawai’i at Manoa

This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr.Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrativeand numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printoutsof the major statistical packages, with annotations to indicate what the numbers mean, encourage interpretationof the results. In addition to demonstrating how to use the packages effectively, the author stresses theimportance of checking the data, assessing the assumptions, and ensuring adequate sample size (by providingguidelines) so that the results can be generalized.

The book is noted for its:� extensive applied coverage of MANOVA;� complete annotated control lines for every analysis;� emphasis on the assumptions underlying the analyses and how to use statistical packages to test these

assumptions;� special attention to statistical power, including numerous tables;� warnings about the danger of capitalization on chance and the need for large samples for reliable results;

and� numerous conceptual, numerical, and computer-related exercises, including answers for half.

The new edition features a CD-ROM with the data sets, updated material on SPSS and SAS throughout thebook, and many new exercises.

Ideal for courses on advanced or multivariate statistics found in psychology, education, and businessdepartments, the book also appeals to practicing researchers with little or no training in multivariate methods.Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge ofmatrix algebra.

Contents: Preface. Introduction. Matrix Algebra. Multiple Regression. Two-Group Multivariate Analysis of Variance. K GroupMANOVA: A Priori and Post Hoc Procedures. Assumptions in MANOVA. Discriminant Analysis. Factorial Analysis ofVariance. Analysis of Covariance. Stepdown Analysis. Confirmatory and Exploratory Factor Analysis. Canonical Correla-tion. Repeated Measures Analysis. Categorical Data Analysis: The Log Linear Model. Appendices: Statistical Tables. DataSets. Obtaining Nonorthogonal Contrasts in Repeated Measures Designs.0-8058-3776-0 [cloth] / 2002 / 712pp. / $110.000-8058-3777-9 [paper] / 2002 / 712pp. / $59.95

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A PRIMER OF MULTIVARIATE STATISTICS TThird EditionRichard J. HarrisUniversity of New Mexico

Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updatedA Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic textcovers multivariate techniques with a taste of latent variable approaches. Throughout the book there is afocus on the importance of describing and testing one’s interpretations of the emergent variables that areproduced by multivariate analysis.

New Features Include:� many more effective examples, computer applications, and infusions of humor throughout the text.� now includes coverage of path analysis and structural equation modeling.� a more detailed discussion of how to construct and interpret linear combinations of sets of independent

and dependent variables and confirmatory factor analysis; and� coverage of recent developments in univariate statistics.

A Primer of Multivariate Statistics, Third Edition retains its conversational writing style while focusing on classicaltechniques. The book gives the reader a feel for why one should consider diving into more detailed treatmentsof computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory fac-tor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of de-scribing and testing one’s interpretations of the emergent variables that are produced by multivariate analysis.

Contents: Preface. The Forest Before the Trees. Multiple Regression: Predicting One Variable From Many. Hotelling’s T2:Tests on One or Two Mean Vectors. Multivariate Analysis of Variance: Differences Among Several Groups on Several Mea-sures. Canonical Correlation: Relationships Between Two Sets of Variables. Principal Component Analysis: RelationshipsWithin a Single Set of Variables. Factor Analysis: The Search for Structure. The Forest Revisited. Digression 1: Finding Maximaand Minima of Polynomials. Digression 2: Matrix Algebra. Digression 3: Solution of Cubic Equations. Appendices: Statisti-cal Tables. Computer Programs. Derivations.0-8058-3210-6 [cloth] / 2001 / 624pp. / $60.00

First Edition received a 1998 CHOICE Outstanding Academic Book AwardSTATISTICAL CONCEPTS TA Second Course for Education and the Behavioral Sciences, Second EditionRichard G. LomaxUniversity of Alabama

“It’s a great text. It explains statistical concepts in some of the most user-friendly English I have ever read in this topicalarea. Definitely check it out.”

—Air Force Research Laboratory Intranet

Richard Lomax provides a conceptual, intuitive approach to the subject that requires only a rudimentaryknowledge of basic algebra. Concepts are clearly stated and supported by real-life examples. Statistical Conceptsfeatures comprehensive coverage in a flexible format so instructors can pick and choose topics. It featurestopics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVAlinear models, expected mean squares in ANOVA models, and stepwise regression. The book features athorough and current discussion of assumptions, the effects of their violations, and how to deal with theirviolation. Designed for a second or intermediate course in statistics for students in education and the behavioralscience, a prerequisite of introductory statistics (descriptive statistics through- t-tests) is assumed.

Contents: Preface. Simple Linear Regression. Multiple Regression. One-Factor Analysis of Variance—Fixed-Effects Model.Multiple-Comparison Procedures. Factorial Analysis of Variance—Fixed-Effects Model. Introduction to Analysis of Covari-ance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Mod-els. Hierarchical and Randomized Block Analysis of Variance Models. Appendix Tables.0-8058-3783-3 [paper] / 2001 / 336pp. / $59.950-8058-3960-7 [Instructor’s Guide] / 2001 / 40pp. / Free Upon Adoption

See AlsoLomax/An Introduction to Statistical Concepts for

Education and Behavioral Sciences, page 5




STATISTICS FOR PSYCHOLOGISTS TAn Intermediate CourseBrian S. EverittInstitute of Psychiatry, King’s College, London

This textbook builds on the introductory statistics courses usually taken by all psychology students. Builtaround a problem solving theme, it extends the intermediate and advanced student’s expertise to morechallenging situations that involve applying statistical methods to real-world problems. Data relevant tothese problems are collected and analyzed to provide useful answers.

Data Sets—Building on its central problem-solving theme, a large number of data sets arising from realproblems are contained in the text and in the exercises provided at the end of each chapter. Answers, or hintsto providing answers, are provided in an appendix.

Mathematical Treatments—Mathematical details of methods are confined to boxed displays which may beignored by the mathematically challenged or studied by those with greater mathematical facility.

Statistical Packages—Concentrating largely on the established SPSS and the newer S-Plus statistical packages,the author provides a short, end-of-chapter section entitled Computer Hints that helps the student undertakethe analyses reported in the chapter using these statistical packages.

Contents: Preface. Statistics in Psychology: Data, Models, and a Little History. Graphical Methods of Displaying Data. Analysisof Variance I: The One-Way Design. Analysis of Variance II: Factorial Designs. Analysis of Repeated Measure Designs. SimpleLinear Regression and Multiple Regression Analysis. Analysis of Longitudinal Data. Distribution-Free and ComputationallyIntensive Methods. Analysis of Categorical Data I: Contingency Tables and the Chi-Square Test. Analysis of Categorical DataII: Log-Linear Models and Logistic Regression. Appendices: Statistical Glossary. Answers to Selected Exercises.0-8058-3836-8 [cloth] / 2001 / 384pp. / $65.00

INTERMEDIATE STATISTICSA Modern Approach, Second EditionJames P. StevensUniversity of Cincinnati

“This is likely to be one of a few stat books that students will not sell...after the course is over. Itis very readable without becoming too technical or buried in symbols and equations.”

—Lynne EdwardsUniversity of Minnesota

“Stevens does an excellent job showing how to use and read computer output....A strength ofthis book is the author’s very clear explanation of power analysis....This is a nice, compact textwith a lot of information contained between the covers....The author’s presentation style is veryreadable and easy to follow.”

—The American Statistician

Intermediate Statistics fully integrates SAS and SPSS. The chapter on factorial ANOVAfeatures thorough discussions of the unequal cell size case and interpreting effects in three-way designs, andan extensive computer example of real data which integrates many of the concepts. In addition, there aresubstantial chapters on covariance and repeated measures analysis. The second edition features a new chapteron multiple regression and Pass 6.0 for power analysis.

Contents: Preface. Introduction. One Way Analysis of Variance. Power Analysis. Factorial Analysis of Variance. RepeatedMeasures Analysis. Simple and Multiple Regression. Analysis of Covariance. Appendices: Data Sets. Statistical Tables. PowerTables.0-8058-2960-1 [cloth + supplement + disk] / 1999 / 432pp. / $99.950-8058-2961-X [paper + supplement + disk] / 1999 / 432pp. / $49.950-8058-3716-7 [Manual-Answers to even numbered exercises] / 1999 / Free Upon Adoption1-56321-337-0 [Data Disk] / 1999 / Free Upon Request0-8058-3891-0 [Supplement] / 2000 / 27pp. / $5.95There are NO discounts if the supplement is sold separately.

Best Seller




STATISTICS IN PSYCHOLOGYAn Historical Perspective, Second EditionMichael CowlesYork University

“The book is chock-full of interesting facts and tidbits and this along with the author’s highly readable writing stylemakes the book difficult to put down. Mathematical level required is minimal and is highly recommended reading forstudents and teachers of statistics.”

—The American Statistician

This book presents an historical overview of the field—from its development to the present—at an accessiblemathematical level. This edition features two new chapters—one on factor analysis and the other on the riseof ANOVA usage is psychological research.

Written for psychology, as well as other social science students, this book introduces the major personalitiesand their roles in the development of the field. It provides insight into the disciplines of statistics andexperimental design through the examination of the character of its founders and the nature of their views,which were sometimes personal and ideological, rather than objective and scientific. It motivates furtherstudy by illustrating the human component of this field, adding dimension to an area that is typically verytechnical.

Intended for advanced undergraduate and/or graduate students in psychology and other social sciences,this book will also be of interest to instructors and/or researchers interested in statistics.

Contents: Preface. The Development of Statistics. Science, Psychology and Statistics. Measurement. The Organization ofData. Probability. Distributions. Practical Inference. Sampling and Estimation. Sampling Distributions. Comparisons, Corre-lations, and Predictions. Factor Analysis. The Design of Experiments. Assessing Differences and Having Confidence. Treat-ments and Effects: The Rise of ANOVA. The Statistical Hotpot.0-8058-3509-1 [cloth] / 2001 / 272pp. / $65.000-8058-3510-5 [paper] / 2001 / 272pp. / $27.50

APPLYING THE RASCH MODELFundamental Measurement in the Human SciencesTrevor G. BondJames Cook UniversityChristine M. FoxUniversity of Toledo

For many researchers the Rasch model provides a very practical solution to data analysis in the social sciences.This volume contends that Rasch measurement is “the model of choice” because it is the closest to realizingthe sort of objective fundamental measurement so long revered in the physical sciences.

The goals of this authored volume are:� to present an accessible overview of the basic properties and principles of rasch analysis, that does not

require a sophisticated statistical background;� to demonstrate how rasch analysis can be applied to a number of generic problems encountered by

psychologists and educators; and� to prepare readers for performing their own analyses and interpreting the results.

This book is ideal for researchers in the human sciences interested in learning how to implement the raschmodel with their own data.

Contents: Preface. Why Measurement Is Fundamental. Important Principles of Measurement Made Explicit. Basic Principlesof the Rasch Model. Building a Set of Items for Measurement. Test Equating: Can Two Tests Measure the Same Ability?Measurement Using Likert Scales. The Partial Credit Rasch Model. Measuring Facets Beyond Ability and Difficulty. Reveal-ing Stage-Based Development. The Rasch Model Applied Across the Human Sciences. Rasch Modeling Applied: RatingScale Design. The Question of Model Fit. A Synthetic Overview. Appendices: Technical Aspects of the Rasch Model. RaschResources.0-8058-3476-1 [cloth] / 2001 / 280pp. / $59.950-8058-4252-7 [paper] / 2001 / 280pp. / $29.95



A FIRST COURSE IN STRUCTURAL EQUATION MODELINGTenko RaykovFordham UniversityGeorge A. MarcoulidesCalifornia State University, Fullerton

”The book is ideal for individuals interested in learning the basics about SEM, evaluating research that employs SEM,and perhaps even performing SEM in subsequent research. The book also serves as an outstanding prerequisite to moreadvanced texts on SEM...”

—Measurement in Physical Education and Exercise Science

Contents: Preface. Fundamentals of Structural Equation Modeling. Getting to Know the EQS and LISREL Programs. PathAnalysis. Confirmatory Factor Analysis. Structural Regression Models. Latent Change Analysis.0-8058-3568-7 [cloth] / 2000 / 216pp. / $59.950-8058-3569-5 [paper] / 2000 / 216pp. / $29.95

Computer Applications

SPSS FOR PSYCHOLOGISTSA Guide to Data Analysis Using SPSS for Windows, Second EditionNicola BraceThe Open UniversityRichard KempUniversity of New South Wales, AustraliaRosemary SnelgarUniversity of Westminster

This second edition of this popular text guides the novice user through the process ofentering and analyzing data using the latest versions of SPSS. The authors assumeonly the most basic knowledge of Windows, review the basic issues regarding designand statistics, and proceed gently through all the major quantitative statisticaltechniques used in psychology, from introductory up to advanced level. Students areintroduced to the rationale and use of each test and provided with clearly annotatedexamples of SPSS output. In this way, they are shown how to choose, perform, andreport the statistical analysis of their own data.

In addition to retaining all the popular elements of the first edition, the new edition:� covers the latest versions of SPSS, Versions 10 and 11, but is also appropriate for those using versions 8

& 9; and� contains more advanced statistical material—ANCOVA, factor analysis, logistic regression and dis-

criminate analysis.

This book is intended for undergraduate students in introductory psychology, statistics/research methodscourses, and other undergraduate-level social science courses.

Contents: Preface Introduction. Data Entry in SPSS. Tests of Difference for Two Sample Designs. Tests of Correlation. Tests ofNominal Data. Data Handling. Analysis of Variance. Multiple Regression. Analysis of Covariance and Multivariate Analysisof Variance. Discriminant Analysis and Logistic Regression. Factor Analysis. Beyond the Basics. Appendices: Data Files.Defining a Variable in SPSS Versions 8 and 9.0-8058-4774-X [paper] / 2003 / 408pp. / $32.50LEA owns rights in US & Canada only.

New Edition


To Preview Select Chapters Online,Visit Our Web site atwww.erlbaum.com


LEVINE’S GUIDE TO SPSSFOR ANALYSIS OF VARIANCESecond EditionMelanie C. PageOklahoma State UniversitySanford L. Braver, David P. MacKinnonArizona State University

A greatly expanded and heavily revised second edition, this popular guide providesinstructions and clear examples for running analyses of variance (ANOVA) and severalother related statistical tests of significance with SPSS. No other guide offers the programstatements required for the more advanced tests in analysis of variance. All of theprograms in the book can be run using any version of SPSS, including versions 11 and11.5. A table at the end of the preface indicates where each type of analysis (e.g., simplecomparisons) can be found for each type of design (e.g., mixed two-factor design).

Providing comprehensive coverage of the basic and advanced topics in ANOVA, this is the only book availablethat provides extensive coverage of SPSS syntax including the commands and subcommands that tell SPSSwhat to do, as well as the pull-down menu point-and-click method (PAC). Detailed explanation of the syntax,including what is necessary, desired, and optional helps ensure that users can validate the analysis beingperformed. The book features the output of each design along with a complete explanation of the relatedprintout.

Features of the second edition include:� reorganized to provide all analysis related to one design type in the same chapter;� expanded coverage of analysis of covariance (ANCOVA) and mixed designs;� new chapters on designs with random factors multivariate designs, and syntax used in PAC;� all new examples of output with complete explanations;� explanations and illustrations for the use of PAC SPSS at the end of each chapter making the simpler

analyses easier to perform; and� a CD-ROM with all of the book’s data sets, as well as exercises for each chapter.

This book is ideal for readers familiar with the basic concepts of the ANOVA technique, including bothpracticing researchers and data analysts, as well as advanced students learning analysis of variance.

Contents: Preface. Using SPSS, and Using This Book. Reading in and Transforming Variables for Analysis in SPSS. One WayAnalysis of Variance. Two Way Analysis of Variance. Three (and Greater) Factor Analysis of Variance. One Factor WithinSubjects Analysis of Variance. Two (or More) Factor Within Subjects Analysis of Variance. Mixed Designs in Analysis ofVariance: One Between Subjects Factor and One Within Subjects Factor. Three (or Greater) Factor Mixed Designs. Analysis ofCovariance. Designs With Random Factors. Multivariate Analysis of Variance: Designs With Multiple Dependent VariablesTested Simultaneously. GLM and UNIANOVA Syntax.0-8058-3096-0 [paper with CD] / 2003 / 216pp. / $39.95Special Discount Price! $22.50Applies if payment accompanies order or for course adoption orders of 5 or more copies.No further discounts apply.

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New Edition Due in 2004SPSS FOR WINDOWS TAn Introduction to Use and Interpretation in ResearchGeorge A. MorganColorado State UniversityOrlando V. GriegoAzusa Pacific UniversityGene W. GloecknerColorado State University

“The labs are very well structured and will enable students to gain mastery over the fundamental principles covered...”—Heather J. MilesStanford University

“The authors’ use of many illustrations of what the computer screen should look like if the commands have been properlyexecuted is excellent...”

—James V. CouchJames Madison University

Designed to help students learn how to analyze and interpret research data, this book demonstrates how toproduce a variety of statistics usually included in basic courses. The authors describe the use and interpretationof these statistics in a nontechnical and jargon-free language.

This book’s main goals are to help the reader choose the appropriate statistics, interpret the outputs, anddevelop skills in writing about the meaning of the results. To achieve these goals, the authors review: (a) howthe appropriate choice of a statistic is based on the design of the research; (b) how to use SPSS to answer anumber of research questions mainly about one realistic data set; and (c) how to interpret SPSS outputs. Thishelps the reader develop skills that cover the whole range of the design, data collection, data entry, analysis,and interpretation process.

The book features:� the key SPSS windows needed to perform the statistical analyses;� complete outputs with call-out boxes and interpretations to point out what to focus on;� interpretation questions to stimulate thinking;� many helpful appendices, and� a Data File CD.

This book uses SPSS 10.0 for Windows. It is intended as a supplemental text in a research methods or statisticscourse in behavioral science or education.

Contents: Preface. Overview SPSS for Windows. Research Problems and Questions. Measurement and Descriptive Statistics.Data Collection. Data Entry and Descriptive Statistics for a Class Questionnaire. Overview of the High School and Beyond(HSB) Data Set, Checking Data, and Descriptive Statistics. Selecting and Interpreting Inferential Statistics. Cross Tabulation,Chi-Square, and Phi (or Cramer’s V). Associating Variables: Pearson and Spearman Correlations. Comparing Groups: t Testsand One-Way ANOVA. Complex Statistics: Factorial ANOVA and Multiple Regression. Appendices: Writing Research Prob-lems and Questions. Developing a Questionnaire and a Data Set. Developing the HSB Codebook. Using Tables and Figuresto Communicate Results. Writing the Methods, Results, and Discussion Sections. Transferring SPSS to and From Word,Power Point, and Excel. Other Useful SPSS Commands. Creating 3-D Graphs and Charts With SPSS. Working With SPSSSyntax (Log) Files. Answers to Interpretation Questions.0-8058-3584-9 [paper with CD] / 2001 / 224pp. / $26.00

Now packaged with S-PLUS 6 for Windows Student EditionUNDERSTANDING STATISTICALCONCEPTS USING S-PLUSRandall E. Schumacker, Allen AkersUniversity of North Texas

A supplemental text for an introductory or intermediate statistics course, each chapter provides a conceptualunderstanding of basic statistics, includes exercises that use S-PLUS simulation programs, and lists a set ofobjectives and a summary. Explanations of how the programs work, with output, are included in each chapter.0-8058-3623-3 [paper with CD] / 2001 / 368pp. / $45.00

To view Table of Contents, go to www.erlbaum.com




CONDUCTING META-ANALYSIS USING SASWinfred Arthur, Jr.Texas A&M UniversityWinston Bennett, Jr.Air Force Research LaboratoryAllen I. HuffcuttBradley UniversityA Volume in the Multivariate Applications Series

“...a ‘must have’ for a researcher or professional interested in writing his or her own program for conducting meta-analysis.”

—Dennis DoverspikeUniversity of Akron

This book reviews the meta-analysis statistical procedure and shows the reader how to conduct one usingSAS. It presents and illustrates the use of the PROC MEANS procedure in SAS to perform the data computationscalled for by the two most commonly used meta-analytic procedures, the Hunter & Schmidt and Glassianapproaches. It serves as both an operational guide and user’s manual by describing and explaining the meta-analysis procedures and then presenting the appropriate SAS program code for computing the pertinentstatistics. The practical, step-by-step instructions quickly prepare the reader to conduct a meta-analysis. Sampleprograms available on the Web further aid the reader in understanding the material. Intended for researchers,students, instructors, and practitioners interested in conducting a meta-analysis, the presentation of bothformulas and their associated SAS program code keeps the reader and user in touch with technical aspects ofthe meta-analysis process. Appropriate for advanced courses in meta-analysis found in psychology, education,management, and other applied social and health sciences departments.

Contents: Preface. The Theory of Meta-Analysis—Sampling Error and the Law of Small Numbers. Meta-Analysis of EffectSizes. Meta-Analysis of Correlations. Outliers in Meta-Analytic Data. Summary and Guidelines for Implementing a Meta-Analysis. Appendices: Reference and Information Sources for the Behavioral and Social Sciences. Equation for Computingthe Pooled Within-Group Standard Deviation. Conversion and Transformation Equations. Upper Percentage Points for theChi-Square Distribution.0-8058-3977-1 [cloth] / 2001 / 200pp. / $45.000-8058-3809-0 [paper] / 2001 / 200pp. / $19.95

STRUCTURAL EQUATIONMODELING WITH AMOSBasic Concepts, Applications, and ProgrammingBarbara M. ByrneUniversity of OttawaA Volume in the Multivariate Applications Series

This book illustrates the ease with which AMOS 4.0 can be used to address researchquestions that lend themselves to structural equation modeling (SEM) by: 1) presentinga non-mathematical introduction to the basic concepts and applications of SEM; 2)demonstrating basic applications of SEM using AMOS 4.0; and 3) high-lighting featuresof AMOS 4.0 that address important caveats related to SEM analyses.

Written in a “user-friendly” style, the author walks the reader through 10 applicationsfrom model specification to estimation to the assessment and interpretation of theoutput. Each application is accompanied by:� a statement of the hypothesis being tested;� a schematic representation of the model under study;� the use and function of a wide variety of icons and pull-down menus;� a full explanation of related AMOS Graphic input models and output files;� a model input file based on AMOS BASIC; and� the published reference from which each application was drawn.Contents: Preface. Part I: Introduction. Structural Equation Models: The Basics. The AMOS Program. Part II: Single-GroupAnalyses. Application 1: Testing for the Factorial Validity of a Theoretical Construct (First-Order CFA Model). Application 2:Testing for the Factorial Validity of Scores From a Measuring Instrument (First-Order CFA Model). Application 3: Testing forthe Factorial Validity of Scores From a Measuring Instrument (Second-Order CFA Model). Application 4: Testing for theValidity of a Causal Structure. Part III: Multiple-Group Analyses. Application 5: Testing for Invariant Factorial Structure of aMeasuring Instrument (First-Order CFA Model). Application 6: Testing for Invariant Factorial Structure of a TheoreticalConstruct (First-Order CFA Model). Application 7: Testing for Invariant Latent Mean Structures. Application 8: Testing forInvariant Pattern of Casual Structure. Part IV: Other Important Topics. Application 9: Bootstrapping as an Aid to Non-normalData. Application 10: Dealing With Incomplete Data. Appendices.0-8058-3322-6 [cloth] / 2001 / 352pp. / $79.950-8058-4104-0 [paper] / 2001 / 352pp. / $39.95

Available inPaperback



THE HANDBOOK OF DATA MININGEdited by

Nong YeArizona State UniversityA Volume in the Human Factors and Ergonomics Series

Advanced technologies have enabled the collection of large amounts of data inmany fields. This data contains valuable information and knowledge that heretoforecould not be used. Up until now, the ability to manually process this large amount ofdata was an unwieldy task. Automated tools were needed to “mine” the usefulinformation from the large amounts of data. Now that such automated tools areavailable, data mining techniques are becoming more popular in many areas of researchand development.

Created with the input of a distinguished International Board of the foremost authoritiesin data mining from academia and industry, The Handbook of Data Mining presentscomprehensive coverage of data mining concepts and techniques. Algorithms,methodologies, management issues, and tools are all illustrated through engagingexamples and real-world applications to ease understanding of the materials. All

necessary materials for data mining, including 245 figures and 72 tables, are conveniently collected in thisone volume enabling the reader to quickly get started conducting research using data mining techniques.The handbook’s 1,164 references provide a road map for further study.

Organized into three parts, Part I presents various data mining methodologies, concepts, and available softwaretools for each methodology. Part II addresses various issues typically faced in the management of data miningprojects and tips on how to maximize outcome utility. Part III features numerous real-world applications ofthese techniques in a variety of areas, including human performance, geospatial, bioinformatics, on- and off-line customer transaction activity, security-related computer audits, network traffic, text and image, andmanufacturing quality.

Ideal for researchers and developers who want to use data mining techniques to derive scientific inferenceswhere extensive data is available in scattered reports and publications. This handbook is also an excellentresource for graduate-level courses on data mining and decision and expert systems methodology.

Contents: G. Salvendy, Foreword. N. Ye, Preface. Part I: Methodologies of Data Mining. J. Gehrke, Decision Trees. G.I. Webb,Association Rules. J. Si, B.J. Nelson, G.C. Runger, Artificial Neural Networks. C.M. Borror, Statistical Analysis of Normaland Abnormal Data. D. Madigan, G. Ridgeway, Bayesian Data Analysis. S.L. Scott, Hidden Markov Processes and Sequen-tial Pattern Mining. G. Ridgeway, Prediction and Classification Models. D.W. Apley, Principal Components and FactorAnalysis. E. Ip, I. Cadez, R. Smyth, Psychometric Methods of Latent Variable Modeling. J. Ghosh, Scalable Clustering. G.Das, D. Gunopulos, Time Series Similarity and Indexing. Y-C. Lai, Z. Liu, N. Ye, T. Yalcinkaya, Nonlinear Time SeriesAnalysis. B-H. Park, H. Kargupta, Distributed Data Mining. Part II: Management of Data Mining. D. Pyle, Data Collection,Preparation, Quality, and Visualization. T. Wu, X. Li, Data Storage and Management. H. Liu, H. Motoda, L. Yu, FeatureExtraction, Selection, and Construction. S.M. Weiss, T. Zhang, Performance Analysis and Evaluation. C. Clifton, Securityand Privacy. R. Grossman, M. Hornick, G. Meyer, Emerging Standards and Interfaces. Part III: Applications of Data Mining.D.A. Nembhard, Mining Human Performance Data. R. Feldman, Mining Text Data. S. Shekhar, R.R. Vatszvai, MiningGeospatial Data. C. Kamath, Mining Science and Engineering Data. M.J. Zaki, Mining Data in Bioinformatics. R. Cooley,Mining Customer-Relationship Management (CRM) Data. N. Ye, Mining Computer and Network Security Data. C. Djeraba,G. Fernandez, Mining Image Data. M.C. Testik, G.C. Runger, Mining Manufacturing Quality Data.0-8058-4081-8 [cloth] / 2003 / 720pp. / $149.95Special Discount Price! $89.95Applies if payment accompanies order or for course adoption orders of 5 or more copies.No further discounts apply.

NewTeaching Resources

Web site:www.erlbaum.com(secure online ordering)

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STOCHASTIC MUSINGSPerspectives From the Pioneers of the Late 20th CenturyEdited by

John PanaretosAthens University, Greece

This new edited volume features contributions from many of the leading scientists inprobability and statistics from the latter part of the 20th century. It is the only book toassemble the views of these leading scientists, the pioneers in their respective fields.Stochastic Musings will appeal to researchers, professionals and students interested inthe history and development of statistics and probability as well as in related areas,such as physics, biometry, economics, and mathematics. Academic and professionalstatisticians will benefit from the book’s coverage of the latest developments in thefield, as well as reflections on the future directions of the discipline.

Contents: V. Barnett, Sample Ordering for Effective Statistical Inference With Particular Referenceto Environmental Issues. D. Bartholomew, A Unified Statistical Approach to Some MeasurementProblems in the Social Sciences. D.R. Cox, Some Remarks on Statistical Aspects of Econometrics. B.Efron, The Statistical Century. D. Freedman, From Association to Causation: Some Remarks on theHistory of Statistics. J. Gani, Scanning a Lattice for a Particular Pattern. D. Karlis, E. Xehalaki,Mixtures Everywhere. L. Kish, New Paradigms (Models) for Probability Sampling S. Kotz, N.L. Johnson, Limit Distribu-tions of Uncorrelated but Dependent Distributions on the Unit Square. I. Moustake, Latent Variable Models with Covariates.S. Nadarajah, S. Kotz, Some New Ellipitical Distributions. C.R. Rao, M.B. Rao, D.N. Shanbhag, On Convex Sets of Multi-variate Distributions and Their Extreme Points. J. Teugels, the Lifespan of a Renewal Z. Tsourti, J. Panaretos, Extreme ValueIndex Estimators and Smoothing Alternatives: A Critical Review. W. Urfer, K. Emrich, Maximum Likelihood Estimates ofGenetic Effects. E. Xekalaki, J. Panaretos, S. Psarakis, A Predictive Model Evaluation and Selection Approach—The Corre-lated Gamma Ratio Distribution. V.M. Zolotarev, Convergence Rate Estimates in Functional Limit Theorems.0-8058-4614-X [cloth] / 2003 / 240pp. / $39.95Special Discount Price! $24.50Applies if payment accompanies order or for course adoption orders of 5 or more copies.No further discounts apply.

ACADEMIC DISHONESTYAn Educator’s GuideBernard E. Whitley, Jr., Patricia Keith-SpiegelBall State University

Academic dishonesty is a critical problem in American education. Unfortunately, mosteducators know little about its causes, steps they can take to prevent and detect it, andhow to handle instances of cheating. This book, written by two nationally renownedscholars in the area of ethics in higher education, is intended to help teachers andadministrators understand and handle these problems.

The book’s goal is to provide readers with a concise handbook covering the full spectrumof issues related to academic dishonesty. To do so, the authors present research andtheory on academic dishonesty and strategies for preventing, confronting, andmanagingthe problem. The following questions are taken into consideration:� Why do students cheat?� What can be done to prevent it?� What are the consequences of ignoring academic dishonesty?� How should suspected students be confronted?� What sanctions are appropriate for students who violate the academic honesty policy?� What can the institution do to encourage a campus ethos of integrity?

Chock-full of practical advice, this book: reviews the existing published literature about academic dishonestyamong college and university students and how faculty members respond to the problem; presents practicaladvice designed to help college and university instructors and administrators deal proactively and effectivelywith academic dishonesty; and considers the broader question of academic integrity as a system-wide issuewithin institutions of higher education.

Contents: Preface. Part I: Definitions, Incidence, Research, and Theory. Academic Dishonesty: The Enemy Within Our Gates.Academic Dishonesty: What Is It and Why Do Students Engage in It? Part II: Applications. Fostering Academic Integrity inthe Classroom. Preventing and Detecting Academic Dishonesty. Confronting and Dealing With Academic Dishonesty. PartIII: Academic Integrity as an Institutional Issue. What Institutions Can Do.0-8058-4019-2 [cloth] / 2002 / 176pp. / $45.000-8058-4020-6 [paper] / 2002 / 176pp. / $19.00

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THE ETHICS OF TEACHINGA Casebook, Second EditionPatricia Keith-Spiegel, Bernard E. Whitley, Jr.,Deborah Ware Balogh, David V. Perkins, Arno F. WittigBall State University

Although college-level educators are trained to be experts in their field, they are oftenill-prepared for the common ethical risks that will frequently confront them in thehalls of academe. Unfortunately, professional ethics codes or institutional policiesusually do not address these common risks. The Ethics of Teaching provides a frankdiscussion of the most frequently encountered ethical dilemmas that can arise ineducational settings, as well as tips on how to avoid these predicaments and how todeal with them when they do occur. The goal is to stimulate discussion and raisefaculties’ consciousness about ethical issues.

Ethical dilemmas are presented as short, engaging case scenarios, most of which arebased on actual situations, so as to furnish more realistic and interesting stimuli forindividual reflection and group discussion. These scenarios offer the opportunity toconsider the subtle complexities inherent in the social and psychological contexts in

which educator-student interactions occur and the effects of those complexities on ethical decision making.Each case is followed by a detailed analysis and advice. The book’s 195 cases are grouped into 22 chaptersrepresenting topics, such as the controversial classroom presentations and assignments, debatable testingand grading practices, problematic student-faculty interactions, dual-role relationships with students, collegialconflicts, managing very difficult students, and confidentiality dilemmas.

The Ethics of Teaching: A Casebook, Second Edition:� focuses on commonly encountered ethical “gray areas” that have no clear solution;� includes questions to stimulate discussion of related ethical issues;� concludes with a chapter on prevention, peer mentoring, and intervention; and� serves as excellent “assigned reading” to stimulate group discussion in teaching workshops and faculty

development programs.

The Ethics of Teaching is ideal for college and university faculty, graduate assistants, and administrators involvedin workshops, graduate teaching assistant courses, and faculty development and new faculty orientationprograms. As a result of the book’s cross-disciplinary development, it will be beneficial to faculty from abroad spectrum of disciplines.

Contents: Preface. Introduction. Part I: The Classroom Ambiance. Instructors’ Classroom Policies. Student Deportment in theClassroom. Part II: The Classroom Learning Experience. Instructors’ Presentation Style and Content. Required In-Class Learn-ing Activities. Part III: Assessments of Students. Testing and Other Academic Evaluations. Grading Methods. Feedback toStudents. Writing Reference Letters for Students. Biased Treatment of Students. Academic Dishonesty. Part IV: Outside theClassroom. Availability to Students. Student-Faculty Interactions. Part V: Relationships in Academia. Multiple Role Relationsand Conflicts of Interest. Interprofessional Relations. Exploitation of Students. Discrimination. Manipulative Students andInstructors. Supervising, Advising, and Collaboration With Students. Part VI: Responsibilities to Students and Colleagues. In-structor Competency. Confidentiality Issues. Political and Public Statements. Responsibilities to the Institution. Afterword:Prevention and Peer Intervention.0-8058-4062-1 [cloth] / 2002 / 296pp. / $59.950-8058-4063-X [paper] / 2002 / 296pp. / $27.50

HANDBOOK FOR TEACHINGSTATISTICS AND RESEARCH METHODSSecond EditionEdited by

Mark E. WareCreighton UniversityCharles L. BrewerFurman University

This volume presents a collection of articles selected from Teaching of Psychology, sponsored by APA Division2. It contains the collective experience of teachers who have successfully dealt with students’ statistics anxiety,resistance to conducting literature reviews, and related problems. For those who teach statistics or researchmethods courses to undergraduate or graduate students in psychology, education, and the social sciences,this book provides many innovative strategies for teaching a variety of methodological concepts andprocedures in statistics and research methods courses.0-8058-3049-9 [paper] / 1999 / 296pp. / $32.50




VISUAL REVELATIONSGraphical Tales of Fate and Deception From Napoleon Bonaparte to Ross PerotHoward WainerNational Board of Medical Examiners

This book is an exploration and celebration of graphical methods of data presentation. Its principal purposeis to enlighten, inform, and amuse the reader regarding the shortcomings of common graphical practices;particularly how they can misinform while simultaneously providing models of wonderful graphics. Thereare many examples of the best graphic practice—graphs that go beyond conveying facts and structure to beable to carry emotion as well.0-8058-3878-3 [cloth] / 2000 / 192pp. / $65.00Special Discount Price! $45.00Applies if payment accompanies order or for course adoption orders of 5 or more copies.No further discounts apply.Reprint From Springer Publishers


UNDERSTANDING STATISTICSStatistical Issues in Psychology,Education, and the Social SciencesEditor

Brian S. EverittInstitute of Psychiatry, King’s College, LondonAssociate Editor

Tenko RaykovFordham University

Editorial ScopeUnderstanding Statistics aims to make psychologists and other behavioral scientistsaware of relevant recent developments in statistics, point out current poor practice intheir use of statistics, illustrate innovative uses of software, highlight software in-adequacies, and generally make nonstatisticians in a variety of disciplines more awareof what modern statistics has to offer them. This journal welcomes well written articlespresenting nontechnical accounts of the use of recently developed statistical methodsin the social and behavioral sciences, as well as articles illustrating the advantages of newer statisticalmethodologies over those traditionally used in these disciplines. In addition, this journal publishes articlesthat point out examples of current bad practice in the application of statistics by researchers in the area anddescribes innovative uses of software.

AudienceResearchers, teachers, and students in psychology, education, and related disciplines, and statisticians givingstatistical courses in these areas.

Volume 2, 2003, QuarterlyCategory Access Type Price US/All Other CountriesIndividual Online & Print $40.00 / $70.00Institution Online & Print $180.00 / $210.00Institution Online Only $160.00 / $160.00Institution Print Only $160.00 / $190.00ISSN: 1534-844XOnline ISSN: 1532-8031

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