Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis, including parametric, nonparametric and semiparametric methods applicable to many types of life history data. Special models such as illness-death, competing risks and progressive processes are considered, as well as more complex models. The book provides both theoretical development and illustrations of analysis based on data from randomized trials and observational cohort studies in health research. It features: Discusses a wide range of applications of multistate models, Presents methods for both continuously and intermittently observed life history processes, Gives a thorough discussion of conditionally independent censoring and observation processes, Discusses models with random effects and joint models for two or more multistate processes, Discusses and illustrates software for multistate analysis that is available in R, Target audience includes those engaged in research and applications involving multistate models.

This groundbreaking book provides students and researchers with a unique overview of the longitudinal study of the development of young people from the ages of 12 to 25. It offers a comprehensive introduction into the multiple theories on the development of the self, personal relationships and psychopathology in adolescence, alongside a non-statistical overview of the many longitudinal models used to study development. The book includes key topics such as the development of the self, adolescent identity and personality; the development of parent-adolescent relationships; friendships and the understanding of others; and the development of psychosocial problems such as anxiety, depression, delinquency, aggression, and substance use. Meeus highlights multiple findings showing how these processes are integrated and identifies eight fundamental patterns of adolescent development to help determine why most adolescents develop into mature and organized individuals towards the end of this life stage, whilst a substantial minority show an inability to mature. It is essential reading for graduate students and researchers in adolescent development and anyone seeking to use longitudinal research methodology in the social and behavioral sciences.

How do young people cope with the multitude of difficult situations and scenarios that are associated with growing up, like anxiety and depression, as well as illness, rejection and family breakdown? How can we facilitate and encourage, through a combination of health, well-being and positive mindset, healthy development during adolescence and beyond? With a substantial focus on the positive aspects of coping, including an emphasis on developing resilience and the achievement of happiness, Erica Frydenberg presents the latest developments in the field of coping. Adolescent Coping highlights the ways in which coping can be measured and implemented in a wide range of circumstances and contexts, with suggestions for the development of coping skills and coping skills training, and it provides strong scholarly evidence for the concepts and constructs that it promotes as providing a pathway to resilience. The work is framed as an ongoing interaction between individuals and their environments as represented by the psychosocial ecological model of Bronfenbrenner. The major theories of coping are articulated that take account of the transactional model, resources theories and proactive models of coping. Areas of recent interest such as neuroscience and epigenetics are included, alongside a new chapter, 'Cyberworld', which provides insights on new and relevant topics such as mindfulness and the impact of social media as they relate to coping in the contemporary context. Adolescent Coping will be of interest to practitioners in psychology, social work, sociology, education and youth and community work as well as to students on courses in adolescent development in these fields.

Diversity-Sensitive Personality Assessment is a comprehensive guide for clinicians to consider how various aspects of client diversity-ethnicity, gender, sexual orientation, age, nationality, religion, regionalism, socioeconomic status, and disability status-can impact assessment results, interpretation, and feedback. Chapters co-written by leading experts in the fields of diversity and personality assessment examine the influence of clinician, client, interpersonal, and professional factors within the assessment context. This richly informed and clinically useful volume encourages clinicians to delve into the complex ways in which individuals' personal characteristics, backgrounds, and viewpoints intersect. This book fills an important gap in the personality assessment literature and is an essential resource for clinicians looking to move beyond surface-level understandings of diversity in assessment.

In this innovative book on autism and gaze from a multimodal interaction perspective, Terhi Korkiakangas examines the role of gaze in everyday situations, asking why eye contact matters, and considering the implications of this crucial question for autism. Since persons on the autism spectrum tend to use it differently and might not engage in eye contact in social situations, gaze is a crucial topic for understanding autism, yet we know surprisingly little about this topic in a real-world context, beyond psychological experiments and the research lab. Drawing on her research on authentic video-recorded social interactions, Korkiakangas shows how a multimodal interaction perspective can shed new light on gaze: what an instance of gaze does, and when, why, and for whom gaze 'matters', from both children on the autism spectrum and their social partners' perspective, including teachers and parents. Grounded in the interactional tradition of conversation analysis, the multimodal interaction perspective offers a major contribution to our understanding of autism by examining communication beyond talk and linguistic resources. Communication, Gaze and Autism considers both mutual gaze and gaze aversion during talk or silence, alongside facial expressions, gestures, and other body movements, to understand what gaze is used for, and to rethink 'eye contact'. The book includes a methodological introduction, practical tools for doing multimodal interaction research, and empirical findings. It also considers the voices of those people on the autism spectrum from the blogosphere, who suggest that eye contact has less significance for them and represents a communication difference, rather than a deficit. This book is designed for anyone with an academic, professional or personal interest in autism. It will particularly appeal to senior undergraduate and graduate students, researchers and practitioners in the fields of communication, social interaction and autism.

Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors' collaborative work in age-period-cohort (APC) analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. The authors show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions. The book makes two essential contributions to quantitative studies of time-related change. Through the introduction of the GLMM framework, it shows how innovative estimation methods and new model specifications can be used to tackle the "model identification problem" that has hampered the development and empirical application of APC analysis. The book also addresses the major criticism against APC analysis by explaining the use of new models within the GLMM framework to uncover mechanisms underlying age patterns and temporal trends. Encompassing both methodological expositions and empirical studies, this book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. It compares new and existing models and methods and provides useful guidelines on how to conduct APC analysis. For empirical illustrations, the text incorporates examples from a variety of disciplines, such as sociology, demography, and epidemiology. Along with details on empirical analyses, software and programs to estimate the models are available on the book's web page.

Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB (R) routines used for the examples are available on the authors' website. The book provides you with the essential background on latent variable models, particularly the latent class model. It discusses how the Markov chain model and the latent class model represent a useful paradigm for latent Markov models. The authors illustrate the assumptions of the basic version of the latent Markov model and introduce maximum likelihood estimation through the Expectation-Maximization algorithm. They also cover constrained versions of the basic latent Markov model, describe the inclusion of the individual covariates, and address the random effects and multilevel extensions of the model. After covering advanced topics, the book concludes with a discussion on Bayesian inference as an alternative to maximum likelihood inference. As longitudinal data become increasingly relevant in many fields, researchers must rely on specific statistical and econometric models tailored to their application. A complete overview of latent Markov models, this book demonstrates how to use the models in three types of analysis: transition analysis with measurement errors, analyses that consider unobserved heterogeneity, and finding clusters of units and studying the transition between the clusters.

Item Response Theory clearly describes the most recently developed IRT models and furnishes detailed explanations of algorithms that can be used to estimate the item or ability parameters under various IRT models. Extensively revised and expanded, this edition offers three new chapters discussing parameter estimation with multiple groups, parameter estimation for a test with mixed item types, and Markov chain Monte Carlo methods. It includes discussions on issues related to statistical theory, numerical methods, and the mechanics of computer programs for parameter estimation, which help to build a clear understanding of the computational demands and challenges of IRT estimation procedures.

This book, originally published in 1970, concerns the new technique of computer simulation in psychology at the time. Computer programs described include models of learning, problem-solving, pattern recognition, the use of language, and personality. More general topics are discussed including the evaluation of such models, the relation of the field to cybernetics, and the problem posed by consciousness. Today it can be read and enjoyed in its historical context.

In this innovative book on autism and gaze from a multimodal interaction perspective, Terhi Korkiakangas examines the role of gaze in everyday situations, asking why eye contact matters, and considering the implications of this crucial question for autism. Since persons on the autism spectrum tend to use it differently and might not engage in eye contact in social situations, gaze is a crucial topic for understanding autism, yet we know surprisingly little about this topic in a real-world context, beyond psychological experiments and the research lab. Drawing on her research on authentic video-recorded social interactions, Korkiakangas shows how a multimodal interaction perspective can shed new light on gaze: what an instance of gaze does, and when, why, and for whom gaze 'matters', from both children on the autism spectrum and their social partners' perspective, including teachers and parents. Grounded in the interactional tradition of conversation analysis, the multimodal interaction perspective offers a major contribution to our understanding of autism by examining communication beyond talk and linguistic resources. Communication, Gaze and Autism considers both mutual gaze and gaze aversion during talk or silence, alongside facial expressions, gestures, and other body movements, to understand what gaze is used for, and to rethink 'eye contact'. The book includes a methodological introduction, practical tools for doing multimodal interaction research, and empirical findings. It also considers the voices of those people on the autism spectrum from the blogosphere, who suggest that eye contact has less significance for them and represents a communication difference, rather than a deficit. This book is designed for anyone with an academic, professional or personal interest in autism. It will particularly appeal to senior undergraduate and graduate students, researchers and practitioners in the fields of communication, social interaction and autism.

Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. The book provides broad, but unified, coverage, and the authors integrate the concepts and ideas shared across models and types of data, especially regarding conceptual links between discrete and continuous limited dependent variables. The authors argue that these dependent variables are, if anything, more common throughout the human sciences than the kind that suit linear regression. They cover special cases or extensions of models, estimation methods, model diagnostics, and, of course, software. They also discuss bounded continuous variables, boundary-inflated models, and methods for modeling heteroscedasticity. Wherever possible, the authors have illustrated concepts, models, and techniques with real or realistic datasets and demonstrations in R and Stata, and each chapter includes several exercises at the end. The illustrations and exercises help readers build conceptual understanding and fluency in using these techniques. At several points the authors bring together material that has been previously scattered across the literature in journal articles, software package documentation files, and blogs. These features help students learn to choose the appropriate models for their purpose.

Notwithstanding the mythical demise of "introspection," self-observation has always been an integral aspect of the social sciences. In the century following the "behavioral revolution," psychology has seen a reduction not so much in the frequency as in the rigor with which self-observation is practiced. A great deal of self-observation has been renamed or obscured (as, for example, "self-report"), but this has served only to defer and impoverish important theoretical and technical work. This volume, which contributes to the development of a rigorous theory of self-observation, is organized around three general objectives: to re-animate a discourse on self-observation through a historical analysis of various self-observation traditions; to outline and begin to address some of the unique theoretical challenges of self-observation; and to elaborate some of the technical and practical details necessary for realizing a program of research dedicated to self-observation. In the first section of the book, three historians of psychology trace the evolution of self-observation. In the second, three scholars who are currently working in contemporary traditions of self-observation discuss the basic theoretical and practical challenges involved in conducting self-observation research. In the final two sections of the book, scholars from the phenomenological and narrative traditions trace the history, theory, and practice of self-observation in their respective traditions. Self-Observation in the Social Sciences continues the fine tradition set by Transaction's History and Theory of Psychology series edited by Jaan Valsiner. It is of interest to psychologists and to those who study methodology within the social sciences.

The Self at Work brings researchers in industrial and organizational psychology and organizational behavior together with researchers in social and personality psychology to explore how the self impacts the workplace. Covering topics such as self-efficacy, self-esteem, self-control, power, and identification, each chapter examines how research on the self informs and furthers understanding of organizational topics such as employee engagement, feedback-seeking, and leadership. With their combined expertise, the chapter authors consider how research on the self has influenced management research and practice (and vice-versa), limitations of applying social psychology research in the organizational realm, and future directions for organizational research on the self. This book is a valuable resource for researchers, graduate students, and professionals who are interested in how research on the self can inform industrial/organizational psychology.

Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data. Techniques are demonstrated through the use of applications that employ cross-national data sets such as the latest European Social Survey. With an emphasis on the generalized latent variable approach, internationally prominent researchers from a variety of fields explain how the methods work, how to apply them, and how they relate to other methods presented in the book. Syntax and graphical and verbal explanations of the techniques are included. Online resources, available at www.routledge.com/9781138690271, include some of the data sets and syntax commands used in the book. Applications from the behavioral and social sciences that use real data-sets demonstrate: The use of samples from 17 countries to validate the resistance to change scale across these nations How to test the cross-national invariance properties of social trust The interplay between social structure, religiosity, values, and social attitudes A comparison of anti-immigrant attitudes and patterns of religious orientations across European countries. The second edition includes six new chapters and two revised ones presenting exciting developments in the literature of cross-cultural analysis including topics such as approximate measurement invariance, alignment optimization, sensitivity analyses, a mixed-methods approach to test for measurement invariance, and a multilevel structural equation modeling approach to explain noninvariance. This book is intended for researchers, practitioners, and advanced students interested in cross-cultural research. Because the applications span a variety of disciplines, the book will appeal to researchers and students in: psychology, political science, sociology, education, marketing and economics, geography, criminology, psychometrics, epidemiology, and public health, as well as those interested in methodology. It is also appropriate for an advanced methods course in cross-cultural analysis.

The transition from school to work is recognized by developmental psychologists as a significant phase in maturation of young people. In the 1990s the likelihood that the transition might be delayed by a period of prolonged unemployment was greater than any time since the 1930s. The psychological consequences of such a delay need to be understood because they may be damaging to both the individual and to society, particularly if they are long-lasting. Such an understanding is essential for the development of sound policy in relation to youth unemployment. Originally published in 1993, Growing up with Unemployment describes a major longitudinal study of a large group of South Australian school leavers through the 1980s. It assesses the scale and context of the problem and reviews the methods and theories that have been developed to study the psychological impact of unemployment. It also looks at those factors which may contribute towards helping young people cope with it, such as financial security, social support and being involved in constructive activities with other people. The authors also examine how we might be able to predict future unemployment and understand the relationship between it and alcohol consumption, smoking and drug use. This book describes a major study with important implications for employment policy, as well as future theory and research. This title will be interesting historical reading for students of psychology and social policy, policy makers and all those who deal with young people.

Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them. Factor analysis in the form of principal components analysis (PCA) or principal factor analysis (PFA) is familiar to most social scientists. However, what is less familiar is understanding that factor analysis is a subset of the more general statistical family of dimension reduction methods. The social scientist's toolkit for factor analysis problems can be expanded to include the range of solutions this book presents. In addition to covering FA and PCA with orthogonal and oblique rotation, this book's coverage includes higher-order factor models, bifactor models, models based on binary and ordinal data, models based on mixed data, generalized low-rank models, cluster analysis with GLRM, models involving supplemental variables or observations, Bayesian factor analysis, regularized factor analysis, testing for unidimensionality, and prediction with factor scores. The second half of the book deals with other procedures for dimension reduction. These include coverage of kernel PCA, factor analysis with multidimensional scaling, locally linear embedding models, Laplacian eigenmaps, diffusion maps, force directed methods, t-distributed stochastic neighbor embedding, independent component analysis (ICA), dimensionality reduction via regression (DRR), non-negative matrix factorization (NNMF), Isomap, Autoencoder, uniform manifold approximation and projection (UMAP) models, neural network models, and longitudinal factor analysis models. In addition, a special chapter covers metrics for comparing model performance. Features of this book include: Numerous worked examples with replicable R code Explicit comprehensive coverage of data assumptions Adaptation of factor methods to binary, ordinal, and categorical data Residual and outlier analysis Visualization of factor results Final chapters that treat integration of factor analysis with neural network and time series methods Presented in color with R code and introduction to R and RStudio, this book will be suitable for graduate-level and optional module courses for social scientists, and on quantitative methods and multivariate statistics courses.

Devising tests that evaluate a nation's educational standing and implement efficacious educational reforms requires a careful balance among the contributions of technology, psychometrics, test design, and the learning sciences. Unlike other forms of adaptive testing, multistage testing (MST) is highly suitable for testing educational achievement because it can be adapted to educational surveys and student testing. Computerized Multistage Testing: Theory and Applications covers the methodologies, underlying technology, and implementation aspects of this type of test design. The book discusses current scientific perspectives and practical considerations for each step involved in setting up an MST program. It covers the history of MST, test design and implementation for various purposes, item pool development and maintenance, IRT-based and classical test theory-based methodologies for test assembly, routing and scoring, equating, test security, and existing software. It also explores current research, existing operational programs, and innovative future assessments using MST. Intended for psychologists, social scientists, and educational measurement scientists, this volume provides the first unified source of information on the design, psychometrics, implementation, and operational use of MST. It shows how to apply theoretical statistical tools to testing in novel and useful ways. It also explains how to explicitly tie the assumptions made by each model to observable (or at least inferable) data conditions. Winner of the 2016 AERA Award for Significant Contribution to Educational Measurement and Research Methodology The 2016 American Education Research Association (AERA) Div. D award committee for Significant Contributions to Educational Measurement and Research Methodology has recognized unanimously this collaborative work advancing the theory and applications of computerized MST. This annual award recognizes published research judged to represent a significant conceptual advancement in the theory and practice of educational measurement and/or educational research methodology. The 2016 award was made under the heading: Measurement, Psychometrics, and Assessment. This collective work, published in 2014 as an edited volume titled Computerized Multistage Testing: Theory and Applications, was cited by the committee both for the originality of the conceptual foundations presented in support of multistage testing and for arguing persuasively for its potential impact on the practice of educational measurement.

This outstanding presentation of the fundamentals of multidimensional scaling illustrates the applicability of MDS to a wide variety of disciplines. The first two sections provide ground work in the history and theory of MDS. The final section applies MDS techniques to such diverse fields as physics, marketing, and political science.

For several decades there has been an increasing move towards viewing the psychotic illnesses from a dimensional perspective, seeing them as continuous with healthy functioning. The idea, concentrating mostly on schizophrenia, has generated considerable theoretical debate as well as empirical research, conducted under the rubric of 'schizotypy'. This book offers a timely discussion of the most significant themes and developments in this research area. Divided into four key sections which represent current concerns in schizotypy research - Measurement, Brain and Biology; Development and Environment; Consequences and Outcomes; and Future Directions - chapters reflect a broad range of approaches and discuss varied theoretical perspectives on schizotypy. Topics include: cognitive and perceptual biases psychometric assessments creativity and schizotypy genetic associations. developmental perspectives Schizotypy: New dimensions will appeal to academics, researchers and postgraduate students in the area of psychotic illnesses, as well as professionals including psychiatrists and clinical psychologists who are concerned with the basis of serious mental disorder. The book will inform readers who are new to the topic and will update and expand the knowledge base of those more experienced in the field.

The Social Cognition and Object Relations Scale-Global Rating Method (SCORS-G) is a clinician rated measure that can be used to code various forms of narrative material. It is comprised of eight dimensions which are scored using a seven-point Likert scale, where lower scores are indicative of more pathological aspects of object representations and higher scores are suggestive of more mature and adaptive functioning. The volume is a comprehensive reference on the 1) validity and reliability of the SCORS-G rating system; 2) in depth review of the empirical literature; 3) administration and intricacies of scoring; and 4) the implications and clinical utility of the system across settings and disciplines for clinicians and researchers.

The Social Cognition and Object Relations Scale-Global Rating Method (SCORS-G) is a clinician rated measure that can be used to code various forms of narrative material. It is comprised of eight dimensions which are scored using a seven-point Likert scale, where lower scores are indicative of more pathological aspects of object representations and higher scores are suggestive of more mature and adaptive functioning. The volume is a comprehensive reference on the 1) validity and reliability of the SCORS-G rating system; 2) in depth review of the empirical literature; 3) administration and intricacies of scoring; and 4) the implications and clinical utility of the system across settings and disciplines for clinicians and researchers.

This book showcases 28 intriguing social psychological experiments that have significantly advanced our understanding of human social thinking and behavior. Each chapter focuses on the details and implications of a single study, while citing related research and real-life examples along the way. All the chapters are fully self-contained, allowing them to be read in any order without loss of coherence. This 2nd Edition contains a number of new studies and, together with its lively, conversational tone, it makes an ideal text for courses in social psychology, introductory psychology, or research design.

A Handbook of Statistical Analyses Using SPSS clearly describes how to conduct a range of univariate and multivariate statistical analyses using the latest version of the Statistical Package for the Social Sciences, SPSS 11. Each chapter addresses a different type of analytical procedure applied to one or more data sets, primarily from the social and behavioral sciences areas. Each chapter also contains exercises relating to the data sets introduced, providing readers with a means to develop both their SPSS and statistical skills. Model answers to the exercises are also provided. Readers can download all of the data sets from a companion Web site furnished by the authors.

Rising life expectancies and declining social capital in the developed world mean that an increasing number of people are likely to experience some form of loneliness in their lifetimes than ever before. Narratives of Loneliness tackles some of the most pressing issues related to loneliness, showing that whilst recent policies on social integration, community building and volunteering may go some way to giving an illusion of not being alone, ultimately, they offer a rhetoric of togetherness that may be more seductive than ameliorative, as the condition and experience of loneliness is far more complex than commonly perceived. Containing thought-provoking contributions from researchers and commentators in several countries, this important work challenges us to rethink some of the burning issues of our day with specific reference to the causes and consequences of loneliness. Topics include the loneliness and mental health of military personnel, loneliness and social media, loneliness and sexuality, urban loneliness, and the experiences of transnational movement and adopted children. This book therefore makes an overdue multidisciplinary contribution to the emerging debate about how best to deal with loneliness in a world that combines greater and faster connectedness on the one hand with more intensely experienced isolation on the other. Since Emile Durkheim first claimed that the structure of society could have a strong bearing on psychological health in the 1890s, researchers in a range of disciplines have explored the probable impact of social context on mental health and wellbeing. Interdisciplinary in approach, Narratives of Loneliness will therefore be of great interest to academics, postgraduate students and researchers in social sciences, the arts, psychology and psychiatry.

Applauded for its clarity, this accessible introduction helps readers apply multilevel techniques to their research. The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software.