Advanced and Multivariate Statistical Methods, Seventh Edition provides conceptual and practical information regarding multivariate statistical techniques to students who do not necessarily need technical and/or mathematical expertise in these methods. This text has three main purposes. The first purpose is to facilitate conceptual understanding of multivariate statistical methods by limiting the technical nature of the discussion of those concepts and focusing on their practical applications. The second purpose is to provide students with the skills necessary to interpret research articles that have employed multivariate statistical techniques. Finally, the third purpose of AMSM is to prepare graduate students to apply multivariate statistical methods to the analysis of their own quantitative data or that of their institutions. New to the Seventh Edition All references to SPSS have been updated to Version 27.0 of the software. A brief discussion of practical significance has been added to Chapter 1. New data sets have now been incorporated into the book and are used extensively in the SPSS examples. All the SPSS data sets utilized in this edition are available for download via the companion website. Additional resources on this site include several video tutorials/walk-throughs of the SPSS procedures. These "how-to" videos run approximately 5-10 minutes in length. Advanced and Multivariate Statistical Methods was written for use by students taking a multivariate statistics course as part of a graduate degree program, for example in psychology, education, sociology, criminal justice, social work, mass communication, and nursing.

This book presents a framework for development, optimization, and evaluation of behavioral, biobehavioral, and biomedical interventions. Behavioral, biobehavioral, and biomedical interventions are programs with the objective of improving and maintaining human health and well-being, broadly defined, in individuals, families, schools, organizations, or communities. These interventions may be aimed at, for example, preventing or treating disease, promoting physical and mental health, preventing violence, or improving academic achievement. This volume introduces the multiphase optimization strategy (MOST), pioneered at The Methodology Center at the Pennsylvania State University, as an alternative to the classical approach of relying solely on the randomized controlled trial (RCT). MOST borrows heavily from perspectives taken and approaches used in engineering, and also integrates concepts from statistics and behavioral science, including the RCT. As described in detail in this book, MOST consists of three phases: preparation, in which the conceptual model underlying the intervention is articulated; optimization, in which experimentation is used to gather the information necessary to identify the optimized intervention; and evaluation, in which the optimized intervention is evaluated in a standard RCT. Through numerous examples, the book demonstrates that MOST can be used to develop interventions that are more effective, efficient, economical, and scalable. Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy is the first book to present a comprehensive introduction to MOST. It will be an essential resource for behavioral, biobehavioral, and biomedical scientists; statisticians, biostatisticians, and analysts working in epidemiology and public health; and graduate-level courses in development and evaluation of interventions.

Contains information for using R software with the examples in the textbook Sampling: Design and Analysis, 3rd edition by Sharon L. Lohr.

This second edition presents the core fundamentals of the subject in 11 manageable chapters while maintaining the book's scientific integrity. The research methods students need to understand, interpret, and analyze social psychological research are emphasized throughout. The streamlined approach provides an economical textbook for students and a flexible format that allows instructors to cover the entire book in a single semester. A book specific Web site contains a free online study guide and a variety of teaching tools. An Instructor's Manual/Test Bank and a Computerized Test Bank are also available.

A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) 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 available that provides extensive coverage of SPSS syntax, including the commands and subcommands that tell SPSS what 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 being performed. The book features the output of each design along with a complete explanation of the related printout. The new edition was reorganized to provide all analysis related to one design type in the same chapter. It now features expanded coverage of analysis of covariance (ANCOVA) and mixed designs, new chapters on designs with random factors, multivariate designs, syntax used in PAC, and all new examples of output with complete explanations. The new edition is accompanied by downloadable resources 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 both practicing researchers and data analysts, as well as advanced students learning analysis of variance.

The distinguishing feature of experimental psychology is not so much the nature of its theories as the methods used to test their validity. The first edition of Experimental Design and Statistics provided a clear and lucid introduction to these methods and the statistical techniques which support them. For this new edition the text has been revised, the coverage of two-sample tests has been extended, and new sections have been added introducing one-sample tests, linear regression and the product-moment correlation coefficient. Problems associated with the applications of experimental design and how to use observations of behaviour in research are key questions for all introductory students of psychology. This new and expanded edition provides them with an invaluable text and source.

Written for graduate level students in advanced statistics, this handbook offers a comprehensive and practical overview of path analysis. A User's Guide to Path Analysis contains: * Definition and graphical illustrations of basic terms and concepts * Illustration of causal diagrams with emphasis on variable positioning, path symbols, error terms, missing arrows, and feedback loops * In-depth discussion of assumptions underlying path analysis * Discussion of causal model estimation with illustrations * Practical research questions for interpreting a path model * Instructions on how to read a path diagram, and how to use the SPSS computer program and interpret the results * Suggestions for what to include when writing up or interpreting findings

Occupational health psychology (OHP) involves the application of psychology to improving the quality of work life and to promoting and protecting the safety, health and well-being of employees. Achieving these aims requires researchers and practitioners to possess in-depth knowledge of the processes that are presumed to bring about the desired outcomes. To date, most studies in OHP have relied on cross-sectional designs in examining these processes. In such designs all variables of interest are measured simultaneously. Although this has generated useful insights in how particular phenomena are associated, such designs cannot be trusted when it comes to drawing causal inferences: association is not causation. This book therefore focuses on longitudinal research designs in OHP, whereby the concepts of interest are measured several times, offering much stronger evidence for causal relationships. The authors focus on design issues in longitudinal research (such as the number of measurements chosen, and the length of the time lags between these measurements), and illustrate these issues in the context of applied research on topics such as the work-family interface, conflict at work, and employee well-being. By doing so this volume provides a state-of-the-art overview of current research in OHP, both in terms of its findings and methodologies. This book is based on a special issue of the journal Work & Stress.

The topic of ego development developed when psychoanalysis did not fulfill all the initial hopes during its early period of prominence. Clinicians--psychiatrists, psychologists, social workers, and counselors--realized that they needed to know more than their patients' or clients' psychopathology or normalcy and their psychosexual behavior and drives. The method for scoring sentence completions presented in this manual was originally developed for a study of women and adolescent girls. By the time it was first published in 1970, however, the method had already come into use in studies of men and boys. Since then, it has been used with widely varying samples, and the test has been translated into several other languages. This wide adoption testifies to the need for such a test. The present version of the manual incorporates three major improvements: * it is based on data from, and is intended for use with, both males and females, * its format is easier to use, and * the examples cited reflect current public attitudes. The format of the scoring manual for the Sentence Completion Test (SCT) is radically changed from the original, making it easier to find the correct rating for a response. The rating scale itself is kept simple and the basic concept of ego development is the same. A tutorial is included to assist in calculating the Total Protocol Ratings (TPRs). ALTERNATIVE BLURB!!! The Washington University Sentence Completion Test, which was developed by Jane Loevinger, is a free-response, semi-projective instrument for the assessment of ego development. The first manual for administering and scoring the test was published in 1970. In addition to its widespread use in the United States, it has also been adopted for use in Canada, the United Kingdom, France, Germany, Italy, the Netherlands, Japan, India, and South Africa. The WUSCT has been used for research in the fields of adolescent personality development, moral development, infancy and parenting, family and gender studies, multiculturalism, religion, psychopathology and psychotherapy, vocational studies, and social and organizational psychology. It is most frequently used by researchers and practitioners in psychology, counseling, social work, and education. This book represents a revised edition of the WUSCT scoring manual, including all items in the 1981 forms, which were revised for use with both men and women. The content reflects current social attitudes, which have changed on some topics since the publication of the original 1970 manual. Although there have been minor changes in terminology, the conception of ego development is unchanged, and the stages of the construct are essentially the same. The format of the scoring manual, however, has been radically changed for ease of use in rating responses. (The rating scale itself, which is the same for all items, is kept simple.) A tutorial is included to assist in calculating the Total Protocol Ratings.

The heart of this book is the translation of The Life Space of the Urban Child, written in 1935 by Martha and Hans Heinrich Muchow. Life Space provides a fresh look at children as actors and how they absorb their city environments. It uses an empirical base connected with theories about the worlds in which children live. The first section provides historical background on Muchow's study and the author. The second section presents the translation of the Life Space study, as well as comments from an environmental psychologist's perspective. The third section reviews the study's theoretical foundations, including the concept of "critical personalism," the perspectives of phenomenology, and the notion of Umwelt (environment). The last section addresses various lines of research developed from the Life Space study, including Muchow's work in describing children in urban environments, methodological approaches, and the significance of space in social science and educational contexts. The manner in which Martha Muchow conducted her studies is itself of note. She obtained access to the children in their environments and combined observation with cartographies and essays produced by the children. This approach was new at the time and continues to inspire researchers today. This volume is the latest work in Transaction's History and Theory of Psychology series.

Looking for a practical, comprehensive overview of Qualitative Research Methods? Want to know the best approach to take for you and your research project? This book takes you through five different qualitative approaches - thematic analysis, interpretative phenomenological analysis, grounded theory, narrative analysis and discourse analysis. Applying them all to a common data set, this book gives you step-by-step guidance on each approach and helps you work out which is the right one for you. Plus, with a whole new part on qualitative data collection - including chapters on interviewing, social media data and visual methodologies - this new edition is the ultimate resource for students engaged in qualitative psychological research or studying methods at any level.

Provides researchers with a reproducible research workflow for using R/RStudio to make the entire researchprocess reproducible; from data gathering, to analysis, to presentation Includes instructions not only for creating reproducible research in R, but also extensively discusses how to take advantage of recent developments in RStudio. Emphasizes the presentation of reproducible research with non-print formats such as HTML5 slideshows, blogs, and other web-based content. Covers a range of techniques to organize and remotely store files at all stages of the research process. These techniques both streamline the research process, especially by making revisions easier, and enhance The book itself will be reproducible, as all of the data, analysis, and markup files will be made available online.

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new approach and apply it to their own research. The book emphasizes conceptual discussions throughout while relegating more technical intricacies to the chapter appendices. Most chapters compare generalized structured component analysis to partial least squares path modeling to show how the two component-based approaches differ when addressing an identical issue. The authors also offer a free, online software program (GeSCA) and an Excel-based software program (XLSTAT) for implementing the basic features of generalized structured component analysis.

Originally published in 1992, the editors of this volume fulfill three main goals: to take stock of progress in the development of data-analysis procedures for single-subject research; to clearly explain errors of application and consider them within the context of new theoretical and empirical information of the time; and to closely examine new developments in the analysis of data from single-subject or small n experiments. To meet these goals, this book provides examples of applicable single-subject research data analysis. It presents a wide variety of topics and perspectives and hopes that readers will select the data-analysis strategies that best reflect their methodological approaches, statistical sophistication, and philosophical beliefs. These strategies include visual analysis, nonparametric tests, time-series experiments, applications of statistical procedures for multiple behaviors, applications of meta-analysis in single-subject research, and discussions of issues related to the application and misapplication of selected techniques.

The Theoretical Framework in Phenomenological Research: Development and Application is an introduction to phenomenology in which the authors overview its origin, main ideas and core concepts. They show the application and relevancy of phenomenological tenets in practical qualitative research, as well as demonstrate how aligning theory and method enhances research credibility. In this detailed but digestible explanation of phenomenological theories, the authors explore the ideas of the main founders pertaining to the meaning of perceived reality and the meaning of being, and how these founders articulated their methodologies. In doing so, The Theoretical Framework in Phenomenological Research fills the well-documented gap between theory and practice within phenomenology by providing a much-needed bridge between the foundational literature and applied research on the subject, focusing equally on theory and practice. The book includes practical demonstrations on how to create theoretical/conceptual frameworks in applied phenomenological research. It also features detailed, step-by-step illustrations and examples regarding how researchers can develop frameworks and use their concepts to inform the development of themes at the data analysis stage. A reliable guide underpinned by foundational phenomenology literature, The Theoretical Framework in Phenomenological Research is an essential text for researchers, instructors, practitioners and students looking to design and conduct phenomenological studies in a manner that ensures credible outcomes.

This book begins with an introductory outline of the structure of the city politics of the United States. There is a study of the city in the federal system, including the politics of feudal aid. This is followed by four case studies: the political roles of mayor, manager, boss and adminstrator-entrepreneur in the city.

Madgwick concludes with some comparative reflections indicating the significance of this study for British local government.

This book was first published in 1970.

This book focuses on how statistical reasoning works and on training programs that can exploit people's natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications are traced in a neural network model of human performance on statistical reasoning problems. This book apppeals to judgment and decision making researchers and other cognitive scientists, as well as to teachers of statistics and probabilistic reasoning.

This new monograph presents Dr. Luce's current understanding of the behavioral properties people exhibit (or should exhibit) when they make selections among alternatives and how these properties lead to numerical representations of those preferences. It summarizes, and places in historical perspective, the research Dr. Luce has done on utility theory for over 10 years. Included are axiomatic theoretical formulations, experiments designed to test individual assumptions, and analyses of the fit to bodies of data of numerical representations derived from the theory.

This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable. It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a "user-friendly" style such that even the "novice" data analyst can easily apply the techniques. Each chapter features: a minimum discussion of mathematical detail; an empirical example applying the technique; and a discussion of the software related to that technique. Content highlights include analysis of mixed, multi-level, structural equation, and categorical data models. It is ideal for researchers, professionals, and students working with repeated measures data from the social and behavioral sciences, business, or biological sciences.

Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event analysis, density estimation, and resampling methods. The text begins with classical nonparametric hypotheses testing, including the sign, Wilcoxon sign-rank and rank-sum, Ansari-Bradley, Kolmogorov-Smirnov, Friedman rank, Kruskal-Wallis H, Spearman rank correlation coefficient, and Fisher exact tests. It then discusses smoothing techniques (loess and thin-plate splines) for classical nonparametric regression as well as binary logistic and Poisson models. The author also describes time-to-event nonparametric estimation methods, such as the Kaplan-Meier survival curve and Cox proportional hazards model, and presents histogram and kernel density estimation methods. The book concludes with the basics of jackknife and bootstrap interval estimation. Drawing on data sets from the author's many consulting projects, this classroom-tested book includes various examples from psychology, education, clinical trials, and other areas. It also presents a set of exercises at the end of each chapter. All examples and exercises require the use of SAS 9.3 software. Complete SAS codes for all examples are given in the text. Large data sets for the exercises are available on the author's website.

Categorical data are quantified as either nominal variables--distinguishing different groups, for example, based on socio-economic status, education, and political persuasion--or ordinal variables--distinguishing levels of interest, such as the preferred politician or the preferred type of punishment for committing burglary. This new book is a collection of up-to-date studies on modern categorical data analysis methods, emphasizing their application to relevant and interesting data sets. This volume concentrates on latent class analysis and item response theory. These methods use latent variables to explain the relationships among observed categorical variables. Latent class analysis yields the classification of a group of respondents according to their pattern of scores on the categorical variables. This provides insight into the mechanisms producing the data and allows the estimation of factor structures and regression models conditional on the latent class structure. Item response theory leads to the identification of one or more ordinal or interval scales. In psychological and educational testing these scales are used for individual measurement of abilities and personality traits. The focus of this volume is applied. After a method is explained, the potential of the method for analyzing categorical data is illustrated by means of a real data example to show how it can be used effectively for solving a real data problem. These methods are accessible to researchers not trained explicitly in applied statistics. This volume appeals to researchers and advanced students in the social and behavioral sciences, including social, developmental, organizational, clinical and health psychologists, sociologists, educational and marketing researchers, and political scientists. In addition, it is of interest to those who collect data on categorical variables and are faced with the problem of how to analyze such variables--among themselves or in relation to metric variables.

Single Case Research in Schools addresses and examines the variety of cutting-edge issues in single case research (SCR) in educational settings. Featuring simple and practical techniques for aggregating data for evidence-based practices, the book delves into methods of selecting behaviors of interest and measuring them reliably. The latter part of Single Case Research in Schools is devoted to a step-by-step model of using SCR to evaluate practices in schools. This includes considerations such as measurement, date collection, length of phases, design consideratoins, calculating effect size and reliability of measures.

This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the program. Modeling syntax is provided in the appendix. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can replicate examples in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568. The book opens with a review of multilevel with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes. These chapters review underlying concepts to assist with trouble-shooting common programming and modeling problems. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with additional trouble shooting techniques and tips for expanding on the modeling techniques introduced. Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors' highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition, this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.

The motivation for this volume in the History and Theory of Psychology series is to look across sub-disciplines within psychology and highlight instances where researchers transcended the tendency to think about methodology along traditional lines. Contributors have located examples of researchers who built upon existing ideas to create methods true to their interests and theoretical convictions.

Emerging Methods in Psychology shows how a discipline creates new methods and carves out possibilities that not only generate data, but also advance knowledge of human psychological functioning. It concentrates on showcasing the possibilities that exist when the researcher focuses on the relationship between theory, method, and data.

The question of what kind of expertise is required is a key issue. This is particularly the case in psychology where the tradition of standardizing methods over the last century has served to stabilize research questions. Knowledge creation is deeply affective and ambiguous rather than the secure accumulation of data by a socially legitimized procedure. This innovative volume moves beyond psychology as social engineering into new varieties of social knowledge.