This volume contains contributions from 24 internationally known scholars covering a broad spectrum of interests in cross-cultural theory and research. This breadth is reflected in the diversity of the topics covered in the volume, which include theoretical approaches to cross-cultural research, the dimensions of national cultures and their measurement, ecological and economic foundations of culture, cognitive, perceptual and emotional manifestations of culture, and bicultural and intercultural processes.

In addition to the individual chapters, the volume contains a dialog among 14 experts in the field on a number of issues of concern in cross-cultural research, including the relation of psychological studies of culture to national development and national policies, the relationship between macro structures of a society and shared cognitions, the integration of structural and process models into a coherent theory of culture, how personal experiences and cultural traditions give rise to intra-cultural variation, whether culture can be validly measured by self-reports, the new challenges that confront cultural psychology, and whether psychology should strive to eliminate culture as an explanatory variable.

Offering an historical perspective on the development of mental health consultation and community mental health, this book's intent is twofold. First, it describes and evaluates Harvard psychiatrist Gerald Caplan's innovative approach to consultation and related activities with respect to the current and future practice of clinical community, school and organizational psychology. Second, it pays tribute to Caplan whose ideas on prevention, crisis theory, support systems, community mental health, mental health consultation and collaboration and population-orientated psychiatry have influenced the practice of professional psychology and allied fields.; The text is divided into three sections: the first provides background information for the remainder of the volume; the second documents Caplan's influence on the way psychology has been applied in various settings; andthe last considers his contribution's present and past influence. The text is aimed at consultant and practising psychologists, community and school psychology graduates and professionals involved with community mental health services.

Brief and inexpensive, this engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Fun interactive Internet exercises that further promote undoing the misconceptions are found on the book's website.

The author s accessible discussion of each misconception has five parts:

• The Misconception - a brief description of the misunderstanding
• Evidence that the Misconception Exists examples and claimed prevalence
• Why the Misconception is Dangerous consequence of having the misunderstanding
• Undoing the Misconception - how to think correctly about the concept
• Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception.

The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook.

Statistical Misconceptions is appropriate for courses taught in a variety of disciplines including psychology, medicine, education, nursing, business, and the social sciences. The book also will benefit independent researchers interested in undoing their statistical misconceptions. "

This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are sustained, in part, upon sound rationale and justification and, in part, upon unfounded lore. Some examples of these "methodological urban legends," as we refer to them in this book, are characterized by manuscript critiques such as: (a) "your self-report measures suffer from common method bias"; (b) "your item-to-subject ratios are too low"; (c) "you can?t generalize these findings to the real world"; or (d) "your effect sizes are too low."

Historically, there is a kernel of truth to most of these legends, but in many cases that truth has been long forgotten, ignored or embellished beyond recognition. This book examines several such legends. Each chapter is organized to address: (a) what the legend is that "we (almost) all know to be true"; (b) what the "kernel of truth" is to each legend; (c) what the myths are that have developed around this kernel of truth; and (d) what the state of the practice should be. This book meets an important need for the accumulation and integration of these methodological and statistical practices.

Brief and inexpensive, this engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Fun interactive Internet exercises that further promote undoing the misconceptions are found on the book's website.

The author s accessible discussion of each misconception has five parts:

• The Misconception - a brief description of the misunderstanding
• Evidence that the Misconception Exists examples and claimed prevalence
• Why the Misconception is Dangerous consequence of having the misunderstanding
• Undoing the Misconception - how to think correctly about the concept
• Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception.

The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook.

Statistical Misconceptions is appropriate for courses taught in a variety of disciplines including psychology, medicine, education, nursing, business, and the social sciences. The book also will benefit independent researchers interested in undoing their statistical misconceptions.

This book reviews methods of conceptualizing, measuring, and analyzing interdependent data in developmental and behavioral sciences. Quantitative and developmental experts describe best practices for modeling interdependent data that stem from interactions within families, relationships, and peer groups, for example. Complex models for analyzing longitudinal data, such as growth curves and time series, are also presented.

Many contributors are innovators of the techniques and all are able to clearly explain the methodologies and their practical problems including issues of measurement, missing data, power and sample size, and the specific limitations of each method.

Featuring a balance between analytic strategies and applications, the book addresses:

• The Actor-Partner Interdependence Model for analyzing influence between two individuals
• The Intraclass Correlational Approach for analyzing distinguishable roles (parent-child) or exchangeable (same-sex) dyadic data
• The Social Relations Model for analyzing group interdependency
• Social Network Analysis approaches for relationships between individuals

This book is intended for graduate students and researchers across the developmental, social, behavioral, and educational sciences. It is an excellent research guide and a valuable resource for advanced methods courses.

This book reviews methods of conceptualizing, measuring, and analyzing interdependent data in developmental and behavioral sciences. Quantitative and developmental experts describe best practices for modeling interdependent data that stem from interactions within families, relationships, and peer groups, for example. Complex models for analyzing longitudinal data, such as growth curves and time series, are also presented.

Many contributors are innovators of the techniques and all are able to clearly explain the methodologies and their practical problems including issues of measurement, missing data, power and sample size, and the specific limitations of each method.

Featuring a balance between analytic strategies and applications, the book addresses:

• The Actor-Partner Interdependence Model for analyzing influence between two individuals
• The Intraclass Correlational Approach for analyzing distinguishable roles (parent-child) or exchangeable (same-sex) dyadic data
• The Social Relations Model for analyzing group interdependency
• Social Network Analysis approaches for relationships between individuals

This book is intended for graduate students and researchers across the developmental, social, behavioral, and educational sciences. It is an excellent research guide and a valuable resource for advanced methods courses.

In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, you'll discover how to characterize complex multivariate data in: Studies involving genetic databases Patterns in the progression of diseases and disabilities Combinations of topics covered by text documents Political ideology or electorate voting patterns Heterogeneous relationships in networks, and much more The handbook spans more than 20 years of the editors' and contributors' statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models.

Meet the challenges of high stakes testing in the practice of school psychology School psychologists can be a positive influence on how students, teachers, parents, schools, and communities cope with the challenges and opportunities associated with high stakes testing. Unfortunately, there has been a significant lack of literature to guide school psychologists and related school-based practitioners on this topic. High Stakes Testing: New Challenges and Opportunities for School Psychology is a timely groundbreaking book that provides useful and thought-provoking information to help psychologists meet the challenges of high stakes testing and create new roles for themselves in helping children succeed. This book discusses practical ways to help provide academic support to facilitate student success on high stakes tests, reduce the impact of stress associated with high stakes testing, assess the data from the tests to improve programs, and take a leadership role in the appropriate use of the tests. The No Child Left Behind Act of 2001(NCLB) and its accountability provisions has helped create and sustain a climate where student performance on state-created achievement tests often has high stakes implications for students, families, and schools. High Stakes Testing: New Challenges and Opportunities for School Psychology provides important background information about high stakes testing, including the legal, historical, and political context of high stakes testing, pertinent psychometrics, and a review of research on academic and non-academic outcomes as it relates to high stakes testing. Using this information as a foundation, the book then identifies new roles and opportunities for school psychologists with respect to high stakes testing. This book is comprehensively referenced. Topics in High Stakes Testing: New Challenges and Opportunities for School Psychology include: advocating for the appropriate use of state-wide assessments the influence of item response theory (IRT) on the development of high stakes tests whether the accountability system of NCLB is truly improving student's learning the impact of high stakes tests on classroom instruction and student motivation strategies for helping students succeed on high stakes tests available resources to cope with the stress of high stakes testing and more High Stakes Testing: New Challenges and Opportunities for School Psychology is a thought-provoking, horizon-expanding resource for school psychologists, public school educators, administrators, school counselors, curriculum coordinators, and special education teachers involved in organizing, administering, and preparing students to take high stakes tests.

Drawing on the work of 75 internationally acclaimed experts in the field, Handbook of Item Response Theory, Three-Volume Set presents all major item response models, classical and modern statistical tools used in item response theory (IRT), and major areas of applications of IRT in educational and psychological testing, medical diagnosis of patient-reported outcomes, and marketing research. It also covers CRAN packages, WinBUGS, Bilog MG, Multilog, Parscale, IRTPRO, Mplus, GLLAMM, Latent Gold, and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton's classic Handbook of Modern Item Response Theory, this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced, with uniform notation, format, and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT.

This handbook reviews promising applications of psychedelics in treatment of such challenging psychiatric problems as posttraumatic stress disorder, major depression, substance use disorders, and end-of-life anxiety. Experts from multiple disciplines synthesize current knowledge on psilocybin, MDMA, ketamine, and other medical hallucinogens. The volume comprehensively examines these substances' neurobiological mechanisms, clinical effects, therapeutic potential, risks, and anthropological and historical contexts. Coverage ranges from basic science to practical clinical considerations, including patient screening and selection, dosages and routes of administration, how psychedelic-assisted sessions are structured and conducted, and management of adverse reactions.

This book presents an update on social psychology as a disciplinary space and research field. First, it discusses the irruption of research methods from other cultural niches in the instituted academic area. Then, the second and third chapters discuss the role of Critical Psychology for community emancipation in hybrid settings and the development of Vygotsky's theory in Latin America. The fourth and fifth chapters offer some questions on contemporary legal and political culture. The sixth and seventh chapters ask how to reconceptualise the studies on Social Imaginary amd childhood. The eighth and ninth chapters present topics as performativity, cybernetic, subjectivities, and technology networks in health-related social support. In the last chapter, the author asks: are networks a cause of the human condition or a result of it? Is virtuality a condition and, at the same time, a result of the human? What could offer a psychoanalytic ethnographic approach to recover the concept of being human as the experience of intimate bonding as part of a social network?

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.

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 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.

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.

"Situational Judgment Tests" advances the science and practice of SJTs by promoting a theoretical framework, providing an understanding of best practices, and establishing a research agenda for years to come. Currently, there is no other source that provides such a comprehensive treatment of situational judgment testing. Key features of this book include:
*chapters rich with theoretical insights and future research possibilities;
*numerous implications for improving the practical applications of SJTs, which include not only SJT development and scoring, but also operational issues affecting test administration and interpretation;
*comprehensive summaries of published and unpublished SJT research; and
*chapters that address topics that are timely and current, such as issues involving the international application of SJTs and technological considerations.
This text is relevant for academics, practitioners, and students of human resource management, organizational behavior, management, andindustrial/organizational psychology. This book is new in  SIOP's Organizational Frontiers Series, publications of the Society of Industrial and Organizational Psychology.

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.