Multiple Imputation in Practice: With Examples Using IVEware provides practical guidance on multiple imputation analysis, from simple to complex problems using real and simulated data sets. Data sets from cross-sectional, retrospective, prospective and longitudinal studies, randomized clinical trials, complex sample surveys are used to illustrate both simple, and complex analyses. Version 0.3 of IVEware, the software developed by the University of Michigan, is used to illustrate analyses. IVEware can multiply impute missing values, analyze multiply imputed data sets, incorporate complex sample design features, and be used for other statistical analyses framed as missing data problems. IVEware can be used under Windows, Linux, and Mac, and with software packages like SAS, SPSS, Stata, and R, or as a stand-alone tool. This book will be helpful to researchers looking for guidance on the use of multiple imputation to address missing data problems, along with examples of correct analysis techniques.

In this collection, international contributors come together to discuss how qualitative and quantitative methods can be used in psychotherapy research. The book considers the advantages and disadvantages of each approach, and recognises how each method can enhance our understanding of psychotherapy. Divided into two parts, the book begins with an examination of quantitative research and discusses how we can transfer observations into numbers and statistical findings. Chapters on quantitative methods cover the development of new findings and the improvement of existing findings, identifying and analysing change, and using meta-analysis. The second half of the book comprises chapters considering how qualitative and mixed methods can be used in psychotherapy research. Chapters on qualitative and mixed methods identify various ways to strengthen the trustworthiness of qualitative findings via rigorous data collection and analysis techniques. Adapted from a special issue of Psychotherapy Research, this volume will be key reading for researchers, academics, and professionals who want a greater understanding of how a particular area of research methods can be used in psychotherapy.

Estimate and Interpret Results from Ordered Regression Models Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives presents regression models for ordinal outcomes, which are variables that have ordered categories but unknown spacing between the categories. The book provides comprehensive coverage of the three major classes of ordered regression models (cumulative, stage, and adjacent) as well as variations based on the application of the parallel regression assumption. The authors first introduce the three "parallel" ordered regression models before covering unconstrained partial, constrained partial, and nonparallel models. They then review existing tests for the parallel regression assumption, propose new variations of several tests, and discuss important practical concerns related to tests of the parallel regression assumption. The book also describes extensions of ordered regression models, including heterogeneous choice models, multilevel ordered models, and the Bayesian approach to ordered regression models. Some chapters include brief examples using Stata and R. This book offers a conceptual framework for understanding ordered regression models based on the probability of interest and the application of the parallel regression assumption. It demonstrates the usefulness of numerous modeling alternatives, showing you how to select the most appropriate model given the type of ordinal outcome and restrictiveness of the parallel assumption for each variable. Web ResourceMore detailed examples are available on a supplementary website. The site also contains JAGS, R, and Stata codes to estimate the models along with syntax to reproduce the results.

The Psychology Research Companion: From student project to working life not only gives you the skills and confidence to conduct your psychology research project at university, but is the first book to show how these skills will help you get ahead in your first job in the workplace. Jessica S. Horst, an American psychologist teaching in the UK, takes you through every step of the research process; from conceiving your research question and choosing a research methodology, to organizing your time and resources effectively. The book includes sections on ethics, data management, working with research participants and report writing, but each chapter is also informed by the wider aim of providing a toolkit for working life. Each chapter is packed with tips and skills that can be taken into the workplace, including working collaboratively and organising your workload, as well as discussing your research project in interview situations and when applying for jobs. This invaluable guide will appeal to all undergraduate and postgraduate psychology students whose aim is to learn a set of transferable research skills as well as to obtain a good degree result.

In this book, William R. Uttal continues his analysis and critique of theories of mind. This book considers theories that are based on macroneural responses (such as those obtained from fMRI) that represent the averaged or cumulative responses of many neurons. The analysis is carried out with special emphasis on the logical and conceptual difficulties in developing a theory but with special attention to some of the current attempts to go from these cumulative responses to explanations of the grand question of how the mind is generated by the brain. While acknowledging the importance of these macroneural techniques in the study of the anatomy and physiology of the brain, Uttal concludes that this macroneural approach is not likely to produce a valid neural theory of cognition because the critical information-the states of the individual neurons-involved in brain activity becoming mental activity is actually lost in the process of summation. Controversial topics are considered in detail including discussions of empirical, logical, and technological barriers to theory building in cognitive neuroscience.

This text introduces teachers to research methods they can use to examine their own classrooms in order to become more effective teachers. Becoming familiar with classroom-based research methods not only enables teachers to do research in their own classrooms, it also provides a basis for assessing the findings of existing research. McKay emphasizes throughout that what a teacher chooses to examine will dictate which method is most effective. Each chapter includes activities to help readers apply the methods described in the chapter, often by analyzing research data. *Chapter I, Classroom Research, introduces the reader to major research purposes and research types as they relate to classroom research, the distinction between quantitative and qualitative research, the formulation of research questions and research designs, and ethical issues in research. *Chapter II, Researching Teachers and Learners, presents research methods that can be used to examine teachers' and learners' attitudes and behaviors: action research, survey research, interviews, verbal reports, diary studies, case studies, and ethnographies. *Chapter III, Researching Classroom Discourse, deals with methods that can be used to study the oral and written discourse of classrooms: interaction analysis, discourse analysis, text analysis, and ways to examine the social and political assumptions underlying the choice and presentation of content in second language teaching materials. *Chapter IV, Writing Research Reports, provides guidelines for both thesis writing and journal articles. Researching Second Language Classrooms is an ideal text for TESOL research methods courses and an essential resource for inservice teachers who wish to undertake classroom research.

* Aims to revive the field study method and demonstrate the importance of studying the behaviour of subjects in real-life, rather than laboratory conditions while complying with the current methodological and ethical standards * Examines the advantages and limitations of the field study method, whilst offering practical guidance on how it can be used in experiments now and in the future * Suitable for graduate and undergraduate students taking courses in methodology, and researchers looking to use field study methods in their research

Choosing Methods in Mental Health Research develops a new framework for mental health research. It is concerned with how to choose the most appropriate mental health research method, not only to address a specific question, but to maximize the potential impact on shaping mental health care. Mike Slade and Stefan Priebe focus attention on the types of audience that the researcher is seeking to influence, the types of evidence each audience accepts as valid, and the relative strengths and limitations of each type of methodology. A range of research methodologies are described and critically appraised, and the use of evidence by different groups is discussed. This produces some important findings about the interplay between research production and consumption, and highlights directions for future mental health research theory and practice. The findings presented here will be relevant to mental health service users and professionals who use research evidence to inform decision-making. It will also prove an invaluable resource for students and researchers in the field of mental health.

This edited volume introduces the latest advances in quantitative methods and illustrates ways to apply these methods to important questions in substance use research. The goal is to provide a forum for dialogue between methodologists developing innovative multivariate statistical methods and substance use researchers who have produced rich data sets. Reflecting current research trends, the book examines the use of longitudinal techniques to measure processes of change over time. Researchers faced with the task of studying the causes, course, treatment, and prevention of substance use and abuse will find this volume helpful for applying these techniques to make optimal use of their data. This innovative volume: introduces the use of latent curve methods for describing individual trajectories of adolescent substance use over time; explores methods for analyzing longitudinal data for individuals nested within groups, such as families, classrooms, and treatment groups; demonstrates how different patterns of missing data influence the interpretation of results; reports on some recent advances in longitudinal growth modeling; illustrates methods to assess mediation when there are multiple mediating pathways underlying an intervention effect; describes methods to identify moderating relations in structural equation models; demonstrates the use of structural equation models to evaluate a preventive intervention; applies epidemic modeling techniques to understand the spread of substance use in society; illustrates the use of latent transition analysis to model substance use as a series of stages; and applies logistic regression to prospectively predict smoking cessation.

This edited volume shows the relationship between dream research and its usefulness in treating patients. Milton Kramer and Myron Glucksman show that there is support for searching for the meaning of dream as experiences extended in time. Dreaming reflects psychological changes and is actually an orderly process, not a random experience. Several chapters in this book explore interviewing methodologies that will help clients reduce the frequency of their nightmares and thus contribute to successful therapy.

This edited volume shows the relationship between dream research and its usefulness in treating patients. Milton Kramer and Myron Glucksman show that there is support for searching for the meaning of dream as experiences extended in time. Dreaming reflects psychological changes and is actually an orderly process, not a random experience. Several chapters in this book explore interviewing methodologies that will help clients reduce the frequency of their nightmares and thus contribute to successful therapy.

Design and Analysis in Educational Research Using jamovi is an integrated approach to learning about research design alongside statistical analysis concepts. Strunk and Mwavita maintain a focus on applied educational research throughout the text, with practical tips and advice on how to do high-quality quantitative research. Based on their successful SPSS version of the book, the authors focus on using jamovi in this version due to its accessibility as open source software, and ease of use. The book teaches research design (including epistemology, research ethics, forming research questions, quantitative design, sampling methodologies, and design assumptions) and introductory statistical concepts (including descriptive statistics, probability theory, sampling distributions), basic statistical tests (like z and t), and ANOVA designs, including more advanced designs like the factorial ANOVA and mixed ANOVA. This textbook is tailor-made for first-level doctoral courses in research design and analysis. It will also be of interest to graduate students in education and educational research. The book includes Support Material with downloadable data sets, and new case study material from the authors for teaching on race, racism, and Black Lives Matter, available at www.routledge.com/9780367723088.

How Can You Improve Your Learning Capabilites? How Can You Enhance Your Potential for Change and Personal Growth? Most of us accept that education does not meet the needs of learners today, or their employers. This mismatch is a key reason why a high level of demotivated youth, as well as workers and managers remain unable to develop themselves. They have been other-organised and are unprepared for the world of work and the challenges of life. First published in 1991, this title offers a radical approach to human learning and personal change. Based on the reflective procedures of Learning Conversations, it enables a deep exploration of the learning process and allows individuals, teams and even whole organisations to create dynamic learning cultures capable of adaptive, constructive and continuing growth. Available again after some years this book is as relevant, if not of greater value, in our ever-changing society than when originally published.

Although many archaeologists have a good understanding of the basics in computer science, statistics, geostatistics, modeling, and data mining, more literature is needed about the advanced analysis in these areas. This book aids archaeologists in learning more advanced tools and methods while also helping mathematicians, statisticians, and computer scientists with no previous knowledge of the field realize the potential of the methods in archaeological experiments.

The editors of this volume suggest that there are missing elements in the conceptualization upon which standard test theory is based. Those elements are models for just how people know what they know and do what they can do, and the ways in which they increase these capacities. Different models are useful for different purposes; therefore, broader or alternative student models may be appropriate. The chapters in this volume consider a variety of directions in which standard test theory might be extended. Topics covered include: the role of test theory in light of recent work in cognitive and educational psychology, test design, student modeling, test analysis, and the integration of assessment and instruction.

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.

This groundbreaking edited book, The Routledge Handbook for Advancing Integration in Mixed Methods Research, presents an array of different integration ideas, with contributions from scholars across the globe. This handbook represents the first major volume that comprehensively discusses this topic of integration. Perhaps the most fundamental and longstanding question in mixed methods research is: How does one best integrate disparate forms of information to produce the best form of inquiry? Each of the 34 seminal chapters in this handbook accelerates the discussion of integration across a broad range of disciplines, including education, arts-based analyses, and work in the Global South, as well as special topics such as psychometrics and media research. Many of the chapters present new topics that have never been written about before, and all chapters offer cutting-edge approaches to integration. They also offer different perspectives of integration - leading the introductory chapter to offer a new and comprehensive definition for integration, as follows: "referring to the optimal mixing, combining, blending, amalgamating, incorporating, joining, linking, merging, consolidating, or unifying of research approaches, methodologies, philosophies, methods, techniques, concepts, language, modes, disciplines, fields, and/or teams within a single study." The concluding chapter offers a meta-framework that accounts for this definition and is designed to help scholars think more about integration in a way that represents a continuous, dynamic, iterative, interactive, synergistic, and holistic meaning-making process. This handbook will be an essential reference work for all scholars and practitioners using or seeking to use mixed methods in their research.

Phil Fennell's tightly argued study traces the history of treatment of mental disorder in Britain over the last 150 years. He focuses specifically on treatment of mental disorder without consent within psychiatric practice, and on the legal position which has allowed it. Treatment Without Consent examines many controversial areas: the use of high-strength drugs and Electro Convulsive Therapy, physical restraint and the vexed issue of the sterilisation of people with learning disabilities. Changing notions of consent are discussed, from the common perception that relatives are able to consent on behalf of the patient, to present-day statutory and common law rules, and recent Law Commission recommendations. This work brings a complex and intriguing area to life; it includes a table of legal sources and an extensive bibliography. It is essential reading for historians, lawyers and all those who are interested in the treatment of mental disorder.

Gathering scholars from different disciplines, this book is the first on how to study emotions using sociological, historical, linguistic, anthropological, psychological, cultural, and mixed approaches. Bringing together the emerging lines of inquiry, it lays foundations for an overdue methodological debate. The volume offers entrancing short essays, richly illustrated with examples and anecdotes, that provide basic knowledge about how to pursue emotions in texts, interviews, observations, spoken language, visuals, historical documents, and surveys. The contributors are respectful of those being researched and are mindful of the effects of their own feelings on the conclusions. The book thus touches upon the ethics of research in vivid first person accounts. Methods are notoriously difficult to teach-this collection fills the gap between dry methods books and students' need to know more about the actual research practice.

The political and legislative changes which took place in South Africa during the 1990s, with the dissolution of apartheid, created a unique set of social conditions. As official policies of segregation were abolished, people of both black and white racial groups began to experience new forms of social contact and intimacy. By examining these emerging processes of intergroup contact in South Africa, and evaluating related evidence from the US, Racial Encounter offers a social psychological account of desegregation. It begins with a critical analysis of the traditional theories and research models used to understand desegregation: the contact hypothesis and race attitude theory. It then analyzes every day discourse about desegregation in South Africa, showing how discourse shapes individuals' conception and management of their changing relationships and acts as a site of ideological resistance to social change. The connection between place, identity and re-creation of racial boundaries emerge as a central theme of this analysis. This book will be of interest to social psychologists, students of intergroup relations and all those interested in post-apartheid South Africa.

CODING MANUAL INFORMATION IS AVAILABLE FROM THE CHAPTER AUTHORS, AND THEIR E-MAIL ADDRESSES CAN BE FOUND ON PAGE XV OF THE BOOK. Family studies is an area that has enjoyed the benefits of conceptual and methodological advances in recent years including the widespread adoption of observational research techniques. The selection of an appropriate coding system is critical to achieving a better understanding of the complex family processes related to normative and pathological development. This book presents 14 examples of family observational coding systems, chosen for the wide range of constructs and phenomena they capture. Each system is described in detail, and excerpts from the coding manual are presented (links to the full coding manuals are available to purchasers of the book at LEA's Web site, www.erlbaum.com). Each chapter follows a consistent outline, so that the different coding systems can be more easily compared to one another. They include the theoretical underpinnings of the measure, its reliability and validity, the coding process, strategies for coder training, and examples of studies in which it has been used. This volume will prove invaluable to students and researchers in family studies, clinicians, and other practitioners who need to interpret data from family observations.

This book focuses on the practical issues and approaches to handling longitudinal and multilevel data. All data sets and the corresponding command files are available via the Web. The working examples are available in the four major SEM packages--LISREL, EQS, MX, and AMOS--and two Multi-level packages--HLM and MLn. All equations and figural conventions are standardized across each contribution. The material is accessible to practicing researchers and students. Users can compare and contrast various analytic approaches to longitudinal and multiple-group data including SEM, Multi-level, LTA, and standard GLM techniques. Ideal for graduate students and practicing researchers in social and behavioral sciences.

Comprehensive and comprehensible, this classic text covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and applying its use. This includes the theory as well as the empirical evaluations. The overall goal is to show readers how to use factor analysis in their substantive research by highlighting when the differences in mathematical procedures have a major impact on the substantive conclusions, when the differences are not relevant, and when factor analysis might not be the best procedure to use. Although the original version was written years ago, the book maintains its relevance today by providing readers with a thorough understanding of the basic mathematical models so they can easily apply these models to their own research. Readers are presented with a very complete picture of the "inner workings" of these methods. The new Introduction highlights the remarkably few changes that the author would make if he were writing the book today. An ideal text for courses on factor analysis or as a supplement for multivariate analysis, structural equation modeling, or advanced quantitative techniques taught in psychology, education, and other social and behavioral sciences, researchers who use these techniques also appreciate this book's thorough review of the basic models. Prerequisites include a graduate level course on statistics and a basic understanding of algebra. Sections with an asterisk can be skipped entirely if preferred.

Comprehensive and comprehensible, this classic text covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and applying its use. This includes the theory as well as the empirical evaluations. The overall goal is to show readers how to use factor analysis in their substantive research by highlighting when the differences in mathematical procedures have a major impact on the substantive conclusions, when the differences are not relevant, and when factor analysis might not be the best procedure to use. Although the original version was written years ago, the book maintains its relevance today by providing readers with a thorough understanding of the basic mathematical models so they can easily apply these models to their own research. Readers are presented with a very complete picture of the "inner workings" of these methods. The new Introduction highlights the remarkably few changes that the author would make if he were writing the book today. An ideal text for courses on factor analysis or as a supplement for multivariate analysis, structural equation modeling, or advanced quantitative techniques taught in psychology, education, and other social and behavioral sciences, researchers who use these techniques also appreciate this book's thorough review of the basic models. Prerequisites include a graduate level course on statistics and a basic understanding of algebra. Sections with an asterisk can be skipped entirely if preferred.

Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter. "

Written for non-mathematically-oriented readers, this text features:

• "
• A description of the data manipulation steps required prior to model estimation so readers can more easily apply the steps to their own data
• An emphasis on how the terminology, interpretation, and estimation" "of familiar general linear models relates to those of more complex models for longitudinal data
• Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers understanding of the overall model-building process
• Sample results sections for each example to provide useful templates for published reports
• Examples using both real and simulated data in the text, along with syntax and output for SPSS, SAS, STATA, and M"plus" at www.PilesOfVariance.com to help readers apply the models to their own data

The book opens with the building blocks of longitudinal analysis general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces "unconditional "longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. "Conditional "longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data.

Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text."