Counselors and psychotherapists are divided about the morality and efficacy of short-term psychotherapy and counseling. This book offers a way through the controversy by giving back the central position to consumers of psychotherapy.
The model of therapy described "Time-Conscious Psychological Therapy" is based on flexible adjustment to the life pattern of the individual client's development. It shows how a carefully structured, stage-based series of therapeutic relationships can be rewarding for both client and therapist. At each stage a clearly stated two-way commitment is entered into by both parties in which the length of time and breadth of focus are related and mutually agreed upon. The process is likely to involve a series of therapeutic encounters with different counselors and psychotherapists and is adaptable to the client's particular needs at any one time. Illustrated throughout by case examples, this is a book for practitioners of all psychological therapies who are looking for a rigorous but flexible approach to empowering their clients.

Hands-on Help is a narrative review of the mushrooming field of computer-aided psychotherapy for mental health problems as a whole, from the time it began in the 1960's through to the present day. The many types of computer-aided psychotherapy and how each might be accessed are detailed together with the pros and cons of such help and the functions it can serve. The authors review prevention as well as treatment.

The book describes and summarizes 97 computer-aided self-help systems in 175 studies according to the types of problem they aim to alleviate. These include phobic, panic, obsessive-compulsive and post-traumatic disorders, depression, anxiety, eating disorders, sexual problems, smoking, alcohol and drug misuse, schizophrenia, insomnia, pain and tinnitus distress, and childhood problems such as encopresis, autism and asthma. Within each type of problem the systems are described according to whether they are used on the internet, CD-ROM, phone, handheld orother device. The final chapter shows how internet self-help systems with phone or email support allow clinics to become more virtual than physical. It also discusses methods of screening suitability and of supporting users, constraints to delivery, uptake and completion, cost-effectiveness, and the place of computer-aided self-help in healthcare provision.

This informative book will be essential reading for psychiatrists, psychologists and all other mental health professionals interested in broadening their understanding of computer-aided psychotherapy.

This timely reference guide is specifically directed toward the needs of second language researchers, who can expect to gain a clearer understanding of which techniques may be most appropriate and fruitful in given research domains. Data Elicitation for Second and Foreign Language Research is a perfect companion to the same author teama (TM)s bestselling Second Language Research: Methodology and Design. It is an indispensable text for graduate or advanced-level undergraduate students who are beginning research projects in the fields of applied linguistics, second language acquisition, and TESOL as well as a comprehensive reference for more seasoned researchers.

This new volume reviews longitudinal models and analysis procedures for use in the behavioral and social sciences. Written by distinguished experts in the field, the book presents the most current approaches and theories, and the technical problems that may be encountered along the way. Readers will find new ideas about the use of longitudinal analysis in solving problems that arise due to the specific nature of the research design and the data available. Divided into two parts, Longitudinal Models in the Behavioral and Related Sciences opens with the latest theoretical developments. In particular, the book addresses situations that arise due to the categorical nature of the data, issues related to state space modeling, and potential problems that may arise from network analysis and/or growth-curve data. The focus of part two is on the application of longitudinal modeling in a variety of disciplines. The book features applications such as heterogeneity on the patterns of a firm's profit, on house prices, and on delinquent behavior; non-linearity in growth in assessing cognitive aging; measurement error issues in longitudinal research; and distance association for the analysis of change. Part two clearly demonstrates the caution that should be taken when applying longitudinal modeling as well as in the interpretation of the results. Longitudinal Models in the Behavioral and Related Sciences is ideal for advanced students and researchers in psychology, sociology, education, economics, management, medicine, and neuroscience.

Quantitative Data Analysis for Language Assessment Volume I: Fundamental Techniques is a resource book that presents the most fundamental techniques of quantitative data analysis in the field of language assessment. Each chapter provides an accessible explanation of the selected technique, a review of language assessment studies that have used the technique, and finally, an example of an authentic study that uses the technique. Readers also get a taste of how to apply each technique through the help of supplementary online resources that include sample data sets and guided instructions. Language assessment students, test designers, and researchers should find this a unique reference as it consolidates theory and application of quantitative data analysis in language assessment.

Age-Period-Cohort analysis has a wide range of applications, from chronic disease incidence and mortality data in public health and epidemiology, to many social events (birth, death, marriage, etc) in social sciences and demography, and most recently investment, healthcare and pension contribution in economics and finance. Although APC analysis has been studied for the past 40 years and a lot of methods have been developed, the identification problem has been a major hurdle in analyzing APC data, where the regression model has multiple estimators, leading to indetermination of parameters and temporal trends. A Practical Guide to Age-Period Cohort Analysis: The Identification Problem and Beyond provides practitioners a guide to using APC models as well as offers graduate students and researchers an overview of the current methods for APC analysis while clarifying the confusion of the identification problem by explaining why some methods address the problem well while others do not. Features * Gives a comprehensive and in-depth review of models and methods in APC analysis. * Provides an in-depth explanation of the identification problem and statistical approaches to addressing the problem and clarifying the confusion. * Utilizes real data sets to illustrate different data issues that have not been addressed in the literature, including unequal intervals in age and period groups, etc. Contains step-by-step modeling instruction and R programs to demonstrate how to conduct APC analysis and how to conduct prediction for the future Reflects the most recent development in APC modeling and analysis including the intrinsic estimator Wenjiang Fu is a professor of statistics at the University of Houston. Professor Fu's research interests include modeling big data, applied statistics research in health and human genome studies, and analysis of complex economic and social science data.

Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal articles make it clear that basic techniques, routinely taught and used, can perform poorly when dealing with skewed distributions, outliers, heteroscedasticity (unequal variances) and curvature. Methods for dealing with these concerns have been derived and can provide a deeper, more accurate and more nuanced understanding of data. A conceptual basis is provided for understanding when and why standard methods can have poor power and yield misleading measures of effect size. Modern techniques for dealing with known concerns are described and illustrated. Features: Presents an in-depth description of both classic and modern methods Explains and illustrates why recent advances can provide more power and a deeper understanding of data Provides numerous illustrations using the software R Includes an R package with over 1300 functions Includes a solution manual giving detailed answers to all of the exercises This second edition describes many recent advances relevant to basic techniques. For example, a vast array of new and improved methods is now available for dealing with regression, including substantially improved ANCOVA techniques. The coverage of multiple comparison procedures has been expanded and new ANOVA techniques are described. Rand Wilcox is a professor of psychology at the University of Southern California. He is the author of 13 other statistics books and the creator of the R package WRS. He currently serves as an associate editor for five statistics journals. He is a fellow of the Association for Psychological Science and an elected member of the International Statistical Institute.

"This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a resource that I am certain will be used by researchers in statistics and related disciplines for quite some time. The discussion of mixtures with heavy tails and asymmetric distributions will place this text as the authoritative, modern reference in the mixture modeling literature." (Douglas Steinley, University of Missouri) Mixture Model-Based Classification is the first monograph devoted to mixture model-based approaches to clustering and classification. This is both a book for established researchers and newcomers to the field. A history of mixture models as a tool for classification is provided and Gaussian mixtures are considered extensively, including mixtures of factor analyzers and other approaches for high-dimensional data. Non-Gaussian mixtures are considered, from mixtures with components that parameterize skewness and/or concentration, right up to mixtures of multiple scaled distributions. Several other important topics are considered, including mixture approaches for clustering and classification of longitudinal data as well as discussion about how to define a cluster Paul D. McNicholas is the Canada Research Chair in Computational Statistics at McMaster University, where he is a Professor in the Department of Mathematics and Statistics. His research focuses on the use of mixture model-based approaches for classification, with particular attention to clustering applications, and he has published extensively within the field. He is an associate editor for several journals and has served as a guest editor for a number of special issues on mixture models.

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.

Missing Data Analysis in Practice provides practical methods for analyzing missing data along with the heuristic reasoning for understanding the theoretical underpinnings. Drawing on his 25 years of experience researching, teaching, and consulting in quantitative areas, the author presents both frequentist and Bayesian perspectives. He describes easy-to-implement approaches, the underlying assumptions, and practical means for assessing these assumptions. Actual and simulated data sets illustrate important concepts, with the data sets and codes available online. The book underscores the development of missing data methods and their adaptation to practical problems. It mainly focuses on the traditional missing data problem. The author also shows how to use the missing data framework in many other statistical problems, such as measurement error, finite population inference, disclosure limitation, combing information from multiple data sources, and causal inference.

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.

This second edition textbook provides invaluable guidance on carrying out qualitative research in psychology using methods both individually and in combination. Suitable for researchers at all stages of their development, the book provides a go-to resource for students who are just starting out, as well as for experienced qualitative researchers planning to carry out research pluralistically. Key features include: *A new chapter on Thematic Analysis *Updated chapters on four other widely used qualitative method - grounded theory, interpretative phenomenological analysis, discourse analysis and narrative analysis *Discussions of the theoretical foundations of qualitative methods employed singly and pluralistically *Consideration of ethical and quality issues pertinent to different methods when used separately and in conjunction *Inclusion of the use of visual and other non-textual data *Problem-based questions *Reflections on practice from experienced researchers The book has been updated throughout to reflect current developments in, and research examples from, the full breadth of the discipline, including from health, social, counselling, and sports and exercise psychology. Studies carried out as part of both academic and professional practice are included, alongside discussion of ways in which researchers from both settings can work together effectively. "This book opens new horizons for innovation, and creates new avenues to explore the complexity of human experience." -Dr Amy Burton, Senior Lecturer in Qualitative Research Methods, Staffordshire University, UK "Frost invites advanced students to move from broad conceptual understandings towards a nuanced appreciation of the potential of qualitative methods in psychology." -Neil Cooper, Professor of Learning and Teaching in Psychology, University of East Anglia, UK "With a crystal clear writing style, Frost enriches our understanding of the practice and experience of doing pluralistic qualitative research - an invaluable contribution." -John McCarthy, Head of School of Applied Psychology, University College Cork, Ireland "Frost has delivered a highly relevant, useful, and contemporary book that will be a prized guide on any qualitative journey." -Brett Smith, Director of Research, Department of Psychology, Durham University, UK "Nollaig Frost has been instrumental to the advancement of a pluralistic perspective in qualitative psychology. This keenly awaited second edition of her book does not disappoint." -Carla Willig, bestselling author of Introducing Qualitative Research in Psychology Nollaig Frost is Adjunct Professor at the School of Applied Psychology, University College Cork, Ireland; Visiting Lecturer at City, University of London, UK; and Visiting Researcher at Middlesex University, UK. She teaches and supervises qualitative research to students at all levels and has led the Pluralism in Qualitative Research (PQR) project since its inception in 2006.

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.

This brilliant CGP book covers all the maths skills needed in AS and A-Level Psychology (the use of maths is required for up to 10% of the marks in the final exams and assessments). It explains Calculations, Graph Skills and Statistics, with clear study notes and step-by-step examples in the context of Psychology. And to make sure you've really got to grips with it all, there are practice questions for each topic - with answers included at the back of the book.

This proceedings volume highlights the latest research and developments in psychometrics and statistics. This book compiles and expands on selected and peer reviewed presentations given at the 83rd Annual International Meeting of the Psychometric Society (IMPS), organized by Columbia University and held in New York, USA July 9th to 13th, 2018. The IMPS is one of the largest international meetings on quantitative measurement in education, psychology and the social sciences. The last couple of years it has attracted more than 500 participants and more than 250 paper presentations from researchers around the world. Leading experts in the world and promising young researchers have written the 38 chapters. The chapters address a large variety of topics including but not limited to item response theory, multistage adaptive testing, and cognitive diagnostic models. This volume is the 7th in a series of recent volumes to cover research presented at the IMPS.

A focused look at the usesand misusesof psychological tests in the context of child custody This book presents an advanced examination of psychological testing and usage in the child custody arena. It addresses test selection issues, provides insightful discussions of how to confront confirmatory biases and avoid the distortion of test findings, and presents clear instructions for the use of specific tests, including MMPI-2 and Rorschach, and a point/counterpoint discussion of the strengths and weaknesses of the Ackerman-Schoendorf Scales for Parent Evaluation of Custody (ASPECT). Psychological Testing in Child Custody Evaluations can be viewed as a work in three parts. The first section addresses theoretical and test usage issues, with chapters focusing on: addressing test selection issues from legal and psychological perspectives bias issues that interfere with the evaluator's ability to collect and consider data objectively a functional, comprehensive approach to the use of psychological tests in a child custody evaluationwith a conceptual framework for choosing assessment techniques to assess parenting competencies and other variables important in forming opinions about custodial placement and visitation access, and a practical example of how to present psychological test data in an advisory report to the court a look at psychological testing from an attorney's point of view The second section of Psychological Testing in Child Custody Evaluations focuses on the MMPI-2 and the Rorschach Inkblot Test in the child custody context, investigating hypotheses that can be inferred from the MMPI-2 regarding parenting behaviors, and the use and value of the Rorschach. This section examines: the foundation from which the MMPI-2 can generate expectations regarding five basic issuesthe quality of attachment and bonding, potential for antisocial behavior, temper control, alienation of affection, and chemical abuse and dependence the range of variables that will generate useful hypotheses regarding parent-child interactions and family systems the effects of the circumstances of litigation on score elevationsincluding recommended limits as to how much elevation can be dismissed as only contextual the important differences between occasion validity and attribute validity the clinical application of an objective interpretation system, including the courtroom credibility of explicit convergent validity the use of the Rorschach in child custody evaluations findings from a study using the Rorschach to address specific parenting variables The third section of Psychological Testing in Child Custody Evaluations is a focused point-counterpoint discussion of ASPECT, between test creator Marc J. Ackerman and Mary Connell, President of the American Academy of Forensic Psychology. This book is essential reading for child custody evaluators, family law attorneys, and judges practicing in the family law arena, as well as educators and students in these fields.

For decades, The Rorschach Inkblot Method (RIM)--the most popular of the projective tests--has been routinely employed for personality assessment and treatment planning. But in recent years, it has not been free from controversy. Criticisms of its validity and empirical support are catalyzing new efforts to strengthen its foundations and document its broad utility. Among the most common--yet also most confusing and challenging--categories of clinical disorders is the personality disorders. However, minimal data have been available on the RIM evaluation of most of those found in DSM-IV. This welcomed book constitutes the first research-grounded, comprehensive guide to the use of the RIM in assessing personality disorders. The first section offers a theoretical overview of personality disorders and constructs a framework and compelling rationale for the legitimate role of the RIM in their assessment. The second, third, and fourth sections present Cluster A disorders--paranoid, schizoid, and schizotypal; Cluster B disorders--antisocial and psychopathic, borderline, histrionic, and narcissistic; and Cluster C disorders--avoidant, dependent, and obsessive-compulsive. The fifth section presents passive aggressive and depressive personality disorders, currently being proposed for DSM inclusion. Each chapter in these four sections includes an extensive description of the disorder, a review of empirical studies of the use of the RIM to assess it, an analysis of the Rorschach variables that may characterize patients diagnosed with it, and a depiction of a real case and discussion of the ways in which the RIM contributed to its formulation. The sixth and final section explores the relationship between psychoanalytic theory and the RIM. Rorschach Assessment of the Personality Disorders brings practical help for clinicians and clinicians-in-training, and suggests new paths for researchers seeking to advance our understanding of the complexities of these disorders.

Individual Differences and Personality provides a student-friendly introduction to both classic and cutting-edge research into personality, mood, motivation and intelligence, and their applications in psychology and in fields such as health, education and sporting achievement. Including a new chapter on 'toxic' personality traits, and an additional chapter on applications in real-life settings, this fourth edition has been thoroughly updated and uniquely covers the necessary psychometric methodology needed to understand modern theories. It also develops deep processing and effective learning by encouraging a critical evaluation of both older and modern theories and methodologies, including the Dark Triad, emotional intelligence and psychopathy. Gardner's and hierarchical theories of intelligence, and modern theories of mood and motivation are discussed and evaluated, and the processes which cause people to differ in personality and intelligence are explored in detail. Six chapters provide a non-mathematical grounding in psychometric principles, such as factor analysis, reliability, validity, bias, test-construction and test-use. With self-assessment questions, further reading and a companion website including student and instructor resources, this is the ideal resource for anyone taking modules on personality and individual differences.

This comprehensive volume explores the set of theoretical, methodological, ethical and analytical issues that shape the ways in which visual qualitative research is conducted in psychology. Using visual data such as film making, social media analyses, photography and model making, the book uniquely uses visual qualitative methods to broaden our understanding of experience and subjectivity. In recent years, visual research has seen a growing emphasis on the importance of culture in experience-based qualitative methods. Featuring contributors from diverse research backgrounds including narrative psychology, personal construct theory and psychoanalysis, the book examines the potential for visual methods in psychology. In each chapter of the book, the contributors explore and address how a visual approach has contributed to existing social and psychological theory in their line of research. The book provides up-to-date insights into combining methods to create new multi-modal methodologies, and analyses these with psychology-specific questions in mind. It covers topics such as sexuality, identity, group processes, child development, forensic psychology, race and gender, and would be the ideal companion for those studying or undertaking research in disciplines like psychology, sociology and gender studies.

This book focuses on quantitative survey methodology, data collection and cleaning methods. Providing starting tools for using and analyzing a file once a survey has been conducted, it addresses fields as diverse as advanced weighting, editing, and imputation, which are not well-covered in corresponding survey books. Moreover, it presents numerous empirical examples from the author's extensive research experience, particularly real data sets from multinational surveys.

This book is in celebration of the seminal work of Roderick P. McDonald whose career has spanned over forty years and three continents. His work in factor analysis, structural modeling, multivariate analysis, and test theory has inspired the research of many of the leading scholars in these fields. All of the book's cutting edge chapters are contributions from Rod's former students, fellow researchers, and/or long time friends. Contemporary Psychometrics features four diverse sections: test theory, factor analysis, structural equation modeling, and multivariate analysis. All of the chapters address key issues in psychometrics using the most contemporary methods possible. The section on test theory includes topics such as multidimensional item response theory (IRT), the relationship between IRT and factor analysis, estimation and testing of these models, and a reflection on basic measurement issues that are often neglected. The factor analysis section reviews the history and development of the model, factorial invariance and factor analysis indeterminacy, and Bayesian inference for factor scores and parameter estimates. latent variable SEM, a survey of goodness of fit assessment, SEM resampling methods, a discussion of how to compare correlations between and within independent samples, the psychological processes with dynamic factor models based on ARMA time series models, and multi-level factor analysis models for continuous and discrete data. The final section on multivariate analysis includes topics such as dual scaling of ordinal data, model specification and missing data problems in time series models, and concludes with a discussion of the themes that run through all multivariate methods. The tour de force through contemporary psychometrics will appeal to advanced students and researchers in the social and behavioral sciences and education, as well as methodologists from other disciplines.

Exner's Comprehensive System has attracted so much attention in recent years that many clinicians and personality researchers are unaware that alternative Rorschach scoring systems exist. This is unfortunate, because some of these systems have tremendous clinical value. Scoring the Rorschach: Seven Validated Systems provides detailed reviews of the best-validated alternative approaches, and points to promising new paths towards the continued growth and refinement of Rorschach interpretation. The editors set the stage with an extended introduction to historical controversies and cutting-edge empirical methods for Rorschach validation. Each chapter presents a different Rorschach scoring system. A brief history is followed by detailed information on scoring and interpretation, a comprehensive summary of evidence bearing on construct validity, and discussion of clinical applications, empirical limitations, and future directions. A user-friendly scoring "manual" for each system offers readers practical guidance. The systems tap a broad array of content areas including ego defenses, thought disorder, mental representations of self and others, implicit motives, personality traits, and potential for psychotherapy. All psychologists seriously engaged in the work of personality assessment will find in this book welcome additions to their professional toolkits.

Drawing on the author’s 45 years of experience in multivariate analysis, Correspondence Analysis in Practice, Third Edition, shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. CA and its variants, subset CA, multiple CA and joint CA, translate two-way and multi-way tables into more readable graphical forms — ideal for applications in the social, environmental and health sciences, as well as marketing, economics, linguistics, archaeology, and more.

Michael Greenacre is Professor of Statistics at the Universitat Pompeu Fabra, Barcelona, Spain, where he teaches a course, amongst others, on Data Visualization. He has authored and co-edited nine books and 80 journal articles and book chapters, mostly on correspondence analysis, the latest being Visualization and Verbalization of Data in 2015. He has given short courses in fifteen countries to environmental scientists, sociologists, data scientists and marketing professionals, and has specialized in statistics in ecology and social science.

Table of Contents

Preface

Scatterplots and Maps

Profiles and the Profile Space

Masses and Centroids

Chi-Square Distance and Inertia

Plotting Chi-Square Distances

Reduction of Dimensionality

Optimal Scaling

Symmetry of Row and Column Analyses

Two-Dimensional Maps

Three More Examples

Contributions to Inertia

Supplementary Points

Correspondence Analysis Biplots

Transition and Regression Relationships

Clustering Rows and Columns

Multiway Tables

Stacked Tables

Multiple Correspondence Analysis

Joint Correspondence Analysis

Scaling Properties of MCA

Subset Correspondence Analysis

Analysis of Matches Matrices

Analysis of Square Tables

Correspondence Analysis of Networks

Data Recoding

Canonical Correspondence Analysis

Co-Inertia and Co-Correspondence Analysis

Aspects of Stability and Inference

Permutation Tests

Appendix A: Theory of Correspondence Analysis

Appendix B: Computation of Correspondence Analysis

Appendix C: Bibliography of Correspondence Analysis

Appendix D: Glossary of Terms

Appendix E: Epilogue

Index

This is the first book devoted to the use of social media and other internet-derived data in forming forensic clinical opinions of behavior. Designed for mental health practitioners, it outlines the challenges and the benefits of incorporating digital information in forensic assessments. It offers best practice guidelines geared to both criminal and civil psycho-legal questions. Each chapter includes a brief overview of the psycho-legal issues, clinical applications of consulting internet-based data, ethical and legal considerations and real life, de-identified case examples. This book provides guidance to the clinician in an emerging technological environment in which there are few resources, and ensures a more scientific and legally sound practice.

Created with the input of a distinguished International Board of the foremost authorities in data mining from academia and industry, "The Handbook of Data Mining" presents comprehensive coverage of data mining concepts and techniques. Algorithms, methodologies, management issues, and tools are all illustrated through engaging examples and real-world applications to ease understanding of the materials.
This book is organized into three parts. Part I presents various data mining methodologies, concepts, and available software tools for each methodology. Part II addresses various issues typically faced in the management of data mining projects and tips on how to maximize outcome utility. Part III features numerous real-world applications of these 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, and manufacturing quality.
This "Handbook" is ideal for researchers and developers who want to use data mining techniques to derive scientific inferences where extensive data is available in scattered reports and publications. It is also an excellent resource for graduate-level courses on data mining and decision and expert systems methodology.