This book explores sexual crime and intellectual functioning. Drawing on expertise from clinical practice and applied research, the volume begins with an exploration of the theoretical and historical background to the interest in links between sexual offending and intellectual functioning. The authors then move on to discuss assessment of intellectual functioning in prison, interventions for low intellectual functioning, autistic spectrum and personality disorder. This book offers a rare insight into the phenomenon of high IQ and sexual offending, a much neglected aspect of the sexual crime literature, and includes novel research that unpacks this link. It further offers an extraordinary insight into the experiences of a person of superior IQ in the criminal justice system for a sexual offence. The book is relevant not only to psychologists, criminologists, social workers and students, but also to practitioners, researchers and the general public with an interest in learning about sexual offending and intellectual functioning.

*Furnishes a thorough introduction and detailed information about the linear regression model, including how to understand and interpret its results, test assumptions, and adapt the model when assumptions are not satisfied. *Uses numerous graphs in R to illustrate the model's results, assumptions, and other features. *Does not assume a background in calculus or linear algebra; rather, an introductory statistics course and familiarity with elementary algebra are sufficient. *Provides many examples using real world datasets relevant to various academic disciplines. *Fully integrates the R software environment in its numerous examples.

Outcome Research and the Future of Psychoanalysis explores the connection between outcome studies and important and complex questions of clinical practices, research methodologies, epistemology, and sociological considerations. Presenting the ideas and voices of leading experts in clinical and extra-clinical research in psychoanalysis, the book provides an overview of the state of the art of outcome research, its results and implications. Furthermore, its contributions discuss the basic premises and ideas of outcome research and in which way the contemporary Zeitgeist might shape the future of psychoanalysis. Divided into three parts, the book begins by discussing the scientific basis of psychoanalysis and advances in psychoanalytic thinking as well as the state of the art of psychoanalytic outcome research, critically analyzing so-called evidence-based therapies. Part II of the book contains exemplary research projects that are discussed from a clinical perspective, illustrating the dialogue between researchers and clinicians. Lastly, in Part III, several psychoanalysts review the importance of critical thinking and research in psychoanalytical education. Thought-provoking and expertly written and researched, this book is a useful resource for academics, researchers and postgraduate students in the fields of mental health, psychotherapy, and psychoanalysis.

The Student Survival Guide for Research Methods in Psychology is designed to support students enrolled in undergraduate or graduate level research methods courses by providing them with the tools they need to succeed. It goes beyond course material to help students engage more fully with research methods content. This survival guide presents clear step-by-step instructions that will help students hone the basic skills to succeed and thrive in their research methods classes and to navigate common pitfalls. The book covers core practical skills, like formatting and writing at an APA standard, understanding research literature (particularly academic journals), using SPSS, and broader skills like how to communicate with your professor, time management, and teamwork skills. It is a highly effective primer text for all psychology students undertaking research methods courses and will also be particularly helpful for students who are currently undertaking these modules and don't feel fully prepared for them.

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.

Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach is aimed at statisticians and quantitative social, economic and public health students and researchers who work with small-area spatial and spatial-temporal data. It assumes a grounding in statistical theory up to the standard linear regression model. The book compares both hierarchical and spatial econometric modelling, providing both a reference and a teaching text with exercises in each chapter. The book provides a fully Bayesian, self-contained, treatment of the underlying statistical theory, with chapters dedicated to substantive applications. The book includes WinBUGS code and R code and all datasets are available online. Part I covers fundamental issues arising when modelling spatial and spatial-temporal data. Part II focuses on modelling cross-sectional spatial data and begins by describing exploratory methods that help guide the modelling process. There are then two theoretical chapters on Bayesian models and a chapter of applications. Two chapters follow on spatial econometric modelling, one describing different models, the other substantive applications. Part III discusses modelling spatial-temporal data, first introducing models for time series data. Exploratory methods for detecting different types of space-time interaction are presented, followed by two chapters on the theory of space-time separable (without space-time interaction) and inseparable (with space-time interaction) models. An applications chapter includes: the evaluation of a policy intervention; analysing the temporal dynamics of crime hotspots; chronic disease surveillance; and testing for evidence of spatial spillovers in the spread of an infectious disease. A final chapter suggests some future directions and challenges. Robert Haining is Emeritus Professor in Human Geography, University of Cambridge, England. He is the author of Spatial Data Analysis in the Social and Environmental Sciences (1990) and Spatial Data Analysis: Theory and Practice (2003). He is a Fellow of the RGS-IBG and of the Academy of Social Sciences. Guangquan Li is Senior Lecturer in Statistics in the Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle, England. His research includes the development and application of Bayesian methods in the social and health sciences. He is a Fellow of the Royal Statistical Society.

1. This book is applicable to courses across the social and behavioral science on a wide range of quantitative methods courses. 2. The book is based on SPSS for EFA - one of the most popular statistics software packages used in behavioral sciences. 3. Clear step-by-step guidance combined with screen shots to show how to apply EFA to real data.

This introduction to visualization techniques and statistical models for second language research focuses on three types of data (continuous, binary, and scalar), helping readers to understand regression models fully and to apply them in their work. Garcia offers advanced coverage of Bayesian analysis, simulated data, exercises, implementable script code, and practical guidance on the latest R software packages. The book, also demonstrating the benefits to the L2 field of this type of statistical work, is a resource for graduate students and researchers in second language acquisition, applied linguistics, and corpus linguistics who are interested in quantitative data analysis.

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.

In Systemic Constellations: Theory, Practice, and Applications, Damian Janus examines systemic constellations, a breakthrough method of psychotherapy, coaching, and consulting developed by Bert Hellinger. Janus examines numerous case studies and addresses the potential of Hellinger's approach for improving clients' mental health.

Advanced Methods in Automatic Item Generation is an up-to-date survey of the growing research on automatic item generation (AIG) in today's technology-enhanced educational measurement sector. As test administration procedures increasingly integrate digital media and Internet use, assessment stakeholders-from graduate students to scholars to industry professionals-have numerous opportunities to study and create different types of tests and test items. This comprehensive analysis offers thorough coverage of the theoretical foundations and concepts that define AIG, as well as the practical considerations required to produce and apply large numbers of useful test items.

Advanced Methods in Automatic Item Generation is an up-to-date survey of the growing research on automatic item generation (AIG) in today's technology-enhanced educational measurement sector. As test administration procedures increasingly integrate digital media and Internet use, assessment stakeholders-from graduate students to scholars to industry professionals-have numerous opportunities to study and create different types of tests and test items. This comprehensive analysis offers thorough coverage of the theoretical foundations and concepts that define AIG, as well as the practical considerations required to produce and apply large numbers of useful test items.

This introduction to visualization techniques and statistical models for second language research focuses on three types of data (continuous, binary, and scalar), helping readers to understand regression models fully and to apply them in their work. Garcia offers advanced coverage of Bayesian analysis, simulated data, exercises, implementable script code, and practical guidance on the latest R software packages. The book, also demonstrating the benefits to the L2 field of this type of statistical work, is a resource for graduate students and researchers in second language acquisition, applied linguistics, and corpus linguistics who are interested in quantitative data analysis.

1. This book is applicable to courses across the social and behavioral science on a wide range of quantitative methods courses. 2. The book is based on SPSS for EFA - one of the most popular statistics software packages used in behavioral sciences. 3. Clear step-by-step guidance combined with screen shots to show how to apply EFA to real data.

This edited volume recognizes that resilience, and the most effective means of harnessing it, differ across individuals, contexts and time. Presenting chapters written by a range of scholars and clinicians, the book highlights effective evidence-based approaches to nurturing resilience, before, during and after a traumatic experience or event. By identifying distinct therapeutic tools which can be used effectively to meet the particular needs and limitations associated with different age groups, clients and types of experience, the volume addresses specific challenges and benefits of nurturing resilience and informs best practice as well as self-care. Approaches explored in the volume include the use of group activities to teach resilience to children, the role of sense-making for victims of sex trafficking, and the ways in which identity and spirituality can be used to help young and older adults in the face of pain and bereavement. Chapters also draw on the lived experiences of those who have engaged in a personal or guided journey towards finding new meaning and achieving posttraumatic growth following experiences of trauma. The rich variety of approaches offered here will be of interest to clinicians, counsellors, scholars and researchers involved in the practice and study of building resilience, as well as trauma studies, psychology and mental health more broadly. The personal and practice-based real-life stories in this volume will also resonate with individuals, family and community members facing adversity.

Featuring a practical approach with numerous examples, the second edition of Categorical Data Analysis for the Behavioral and Social Sciences focuses on helping the reader develop a conceptual understanding of categorical methods, making it a much more accessible text than others on the market. The authors cover common categorical analysis methods and emphasize specific research questions that can be addressed by each analytic procedure, including how to obtain results using SPSS, SAS, and R, so that readers are able to address the research questions they wish to answer. Each chapter begins with a "Look Ahead" section to highlight key content. This is followed by an in-depth focus and explanation of the relationship between the initial research question, the use of software to perform the analyses, and how to interpret the output substantively. Included at the end of each chapter are a range of software examples and questions to test knowledge. New to the second edition: The addition of R syntax for all analyses and an update of SPSS and SAS syntax. The addition of a new chapter on GLMMs. Clarification of concepts and ideas that graduate students found confusing, including revised problems at the end of the chapters. Written for those without an extensive mathematical background, this book is ideal for a graduate course in categorical data analysis taught in departments of psychology, educational psychology, human development and family studies, sociology, public health, and business. Researchers in these disciplines interested in applying these procedures will also appreciate this book's accessible approach.

Over the course of recent decades, scholars and practitioners have been working to integrate contemporary psychology-related fields and Christianity. This project continues to move forward, evidenced in associations, publications, degree programs, and conferences around the world. While much progress has been made, there are still foundational issues to be worked out and aspects of integration the community is just now venturing into. In this expert overview, psychologists William L. Hathaway and Mark A. Yarhouse take stock of the integration project to date, provide an introduction for those who wish to come on board, highlight work yet to be done, and offer a framework to strategically organize next steps. The authors' attention encompasses five domains: worldview integration theoretical integration applied integration role integration personal integration Their comprehensive approach yields insights relevant for non-clinical areas of psychological science as well as for counseling, social work, and other related mental health fields. Done properly, integration enriches our understanding of both Christianity and psychology. Through biblical and theological grounding and numerous examples, Hathaway and Yarhouse demonstrate how synthesis can continue to serve the field and make a difference in caring for individual lives. Christian Association for Psychological Studies (CAPS) Books explore how Christianity relates to mental health and behavioral sciences including psychology, counseling, social work, and marriage and family therapy in order to equip Christian clinicians to support the well-being of their clients.

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.

Quantitative Data Analysis for Language Assessment Volume II: Advanced Methods demonstrates advanced quantitative techniques for language assessment. The volume takes an interdisciplinary approach and taps into expertise from language assessment, data mining, and psychometrics. The techniques covered include Structural Equation Modeling, Data Mining, Multidimensional Psychometrics and Multilevel Data Analysis.Volume II is distinct among available books in language assessment, as it engages the readers in both theory and application of the methods and introduces relevant techniques for theory construction and validation. This book is highly recommended to graduate students and researchers who are searching for innovative and rigorous approaches and methods to achieve excellence in their dissertations and research. It is also a valuable source for academics who teach quantitative approaches in language assessment and data analysis courses.

The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.

Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.

Capture-recapture methods have been used in biology and ecology for more than 100 years. However, it is only recently that these methods have become popular in the social and medical sciences to estimate the size of elusive populations such as illegal immigrants, illicit drug users, or people with a drinking problem. Capture-Recapture Methods for the Social and Medical Sciences brings together important developments which allow the application of these methods. It has contributions from more than 40 researchers, and is divided into eight parts, including topics such as ratio regression models, capture-recapture meta-analysis, extensions of single and multiple source models, latent variable models and Bayesian approaches. The book is suitable for everyone who is interested in applying capture-recapture methods in the social and medical sciences. Furthermore, it is also of interest to those working with capture-recapture methods in biology and ecology, as there are some important developments covered in the book that also apply to these classical application areas.

Learn How to Infuse Leadership into Your Passion for Scientific Research Leadership and Women in Statistics explores the role of statisticians as leaders, with particular attention to women statisticians as leaders. By paying special attention to women's issues, this book provides a clear vision for the future of women as leaders in scientific and technical fields. It also shows how emerging and current leaders of both genders in many disciplines can expand their leadership potentials. Featuring contributions from leadership experts and statisticians at various career stages, this unique and insightful text: Examines leadership within the roles of statistician and data scientist from international and diverse perspectives Supplies a greater understanding of leadership within teams, research consulting, and project management Encourages reflection on leadership behaviors, promoting both natural and organizational leadership Identifies existing opportunities to foster creative outputs and develop strong leadership voices Includes real-life stories about overcoming barriers to leadership Leadership and Women in Statistics explains how to convert a passion for statistical science into visionary, ethical, and transformational leadership. Although the context focuses on statistics, the material applies to almost all fields of endeavor. This book is a valuable resource for those ready to consider leadership as an important element of their careers, and for those who are already leaders but want to deepen their perspectives on leadership. It makes an ideal text for group leadership training as well as for individual professional development.

A Sound Basis for the Theory of Statistical Inference Measuring Statistical Evidence Using Relative Belief provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It shows that being explicit about how to measure statistical evidence allows you to answer the basic question of when a statistical analysis is correct. The book attempts to establish a gold standard for how a statistical analysis should proceed. It first introduces basic features of the overall approach, such as the roles of subjectivity, objectivity, infinity, and utility in statistical analyses. It next discusses the meaning of probability and the various positions taken on probability. The author then focuses on the definition of statistical evidence and how it should be measured. He presents a method for measuring statistical evidence and develops a theory of inference based on this method. He also discusses how statisticians should choose the ingredients for a statistical problem and how these choices are to be checked for their relevance in an application.

In 1968, Stanley Kubrick completed and released his magnum opus motion picture 2001: A Space Odyssey; a time that was also tremendously important in the formation of the psychoanalytic theory of Jacques Lacan. Bringing these figures together, Bristow offers a study that goes beyond, as the film did. He extends Lacan's late topological insights, delves into conceptualisations of desire, in G. W. F. Hegel, Alexandre Kojeve, and Lacan himself, and deals with the major themes of cuts (filmic and psychoanalytic); space; silence; surreality; and 'das Ding', in relation to the movie's enigmatic monolith. This book is a tour de force of psychoanalytic theory and space odyssey that will appeal to academics and practitioners of psychoanalysis and film studies, as well as to any fan of Kubrick's work.