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.

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 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 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.

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

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.

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.

The normal distribution is widely known and used by scientists and engineers. However, there are many cases when the normal distribution is not appropriate, due to the data being skewed. Rather than leaving you to search through journal articles, advanced theoretical monographs, or introductory texts for alternative distributions, the Handbook of Exponential and Related Distributions for Engineers and Scientists provides a concise, carefully selected presentation of the properties and principles of selected distributions that are most useful for application in the sciences and engineering. The book begins with all the basic mathematical and statistical background necessary to select the correct distribution to model real-world data sets. This includes inference, decision theory, and computational aspects including the popular Bootstrap method. The authors then examine four skewed distributions in detail: exponential, gamma, Weibull, and extreme value. For each one, they discuss general properties and applicability to example data sets, theoretical characterization, estimation of parameters and related inferences, and goodness of fit tests. The final chapter deals with system reliability for series and parallel systems. Presenting methods based on statistical simulations and numerical computations, the Handbook of Exponential and Related Distributions for Engineers and Scientists supplies hands-on tools for applied researchers in need of practical tools for data analysis.

Emerging from a qualitative research study on the rehabilitation experiences of adult male probationers with mental health illness, this book describes the treatment and rehabilitation experiences of these individuals and contextualizes their experiences within the landscape of mental health treatment in the United States. Often underserved in outpatient community support programs, probationers with mental health illness (PMIs) face stigma and obstacles in seeking mental health treatment and rehabilitation. Examining the lived experiences of both PMIs and their probation officers, this book offers insights into the study of stigma as it relates to probationers and the work of probation officers in furthering treatment and rehabilitation options for PMIs.

The development of communication as a discipline has resulted in an explosion of scales tapping various aspects of interpersonal, mass, organizational, and instructional communication. These scales are scattered across a bewildering array of journals, books, dissertations, and research reports--a situation that often hinders awareness and use of particular measures. Intended as a partial remedy to the situation, this sourcebook brings together a variety of scales that measure a number of important communication constructs. The scales presented are drawn from areas of interpersonal, mass, organizational, and instructional communication--areas in which the use of formal, quantitative scales is particularly well developed. "Communication Research Measures" reflects the recent important emphasis on developing and improving the measurement base of the communication discipline. It results in an equal amount of labor saved on the part of the scholars, students, and practitioners who find this book useful, and it contributes in a significant way to research efforts.
Originally published by Guilford Press in 1994, now available from LEA.

Practical Handbook of Curve Fitting is a reference work assembled by Arlinghaus and a set of editors with well over a century of combined experience in various disciplines and activities related to curve fitting. The book demonstrates how to analyze World data bases and graph and map the results. Default settings in software packages can produce attractive graphs of data imported into the software. Often, however, the default graph has no equation associated with it and cannot therefore be used as a tool for further analysis or projection of the data. The same software can often be used to generate curves from equations. The reader is shown directly, and in a series of steps, how to fit curves to data using Lotus 1-2-3. There are traditional unbounded curve fitting techniques-lines of least squares, exponentials, logistic curves, and Gompertz curves. There is the bounded curve fitting technique of cubic spline interpolation. Beyond these, there is a detailed application of Feigenbaum's graphical analysis from chaos theory, and there is a hint as to how fractal geometry might come into play. Curve fitting algorithms take on new life when they are actually used on real-world data. They are used in numerous worked examples drawn from electronic data bases of public domain information from the Stars data base of The World Bank and from the WRD data base of the World Resources Institute. The applications are current and reflect a state-of-the-art interest in the human dimensions of global change.

Interviewer Effects from a Total Survey Error Perspective presents a comprehensive collection of state-of-the-art research on interviewer-administered survey data collection. Interviewers play an essential role in the collection of the high-quality survey data used to learn about our society and improve the human condition. Although many surveys are conducted using self-administered modes, interviewer-administered modes continue to be optimal for surveys that require high levels of participation, include difficult-to-survey populations, and collect biophysical data. Survey interviewing is complex, multifaceted, and challenging. Interviewers are responsible for locating sampled units, contacting sampled individuals and convincing them to cooperate, asking questions on a variety of topics, collecting other kinds of data, and providing data about respondents and the interview environment. Careful attention to the methodology that underlies survey interviewing is essential for interviewer-administered data collections to succeed. In 2019, survey methodologists, survey practitioners, and survey operations specialists participated in an international workshop at the University of Nebraska-Lincoln to identify best practices for surveys employing interviewers and outline an agenda for future methodological research. This book features 23 chapters on survey interviewing by these worldwide leaders in the theory and practice of survey interviewing. Chapters include: The legacy of Dr. Charles F. Cannell's groundbreaking research on training survey interviewers and the theory of survey interviewing Best practices for training survey interviewers Interviewer management and monitoring during data collection The complex effects of interviewers on survey nonresponse Collecting survey measures and survey paradata in different modes Designing studies to estimate and evaluate interviewer effects Best practices for analyzing interviewer effects Key gaps in the research literature, including an agenda for future methodological research Chapter appendices available to download from https://digitalcommons.unl.edu/sociw/ Written for managers of survey interviewers, survey methodologists, and students interested in the survey data collection process, this unique reference uses the Total Survey Error framework to examine optimal approaches to survey interviewing, presenting state-of-the-art methodological research on all stages of the survey process involving interviewers. Acknowledging the important history of survey interviewing while looking to the future, this one-of-a-kind reference provides researchers and practitioners with a roadmap for maximizing data quality in interviewer-administered surveys.

Collecting and analyzing data on unemployment, inflation, and inequality help describe the complex world around us. When published by the government, such data are called official statistics. They are reported by the media, used by politicians to lend weight to their arguments, and by economic commentators to opine about the state of society. Despite such widescale use, explanations about how these measures are constructed are seldom provided for a non-technical reader. This Measuring Society book is a short, accessible guide to six topics: jobs, house prices, inequality, prices for goods and services, poverty, and deprivation. Each relates to concepts we use on a personal level to form an understanding of the society in which we live: We need a job, a place to live, and food to eat. Using data from the United States, we answer three basic questions: why, how, and for whom these statistics have been constructed. We add some context and flavor by discussing the historical background. This book provides the reader with a good grasp of these measures. Chaitra H. Nagaraja is an Associate Professor of Statistics at the Gabelli School of Business at Fordham University in New York. Her research interests include house price indices and inequality measurement. Prior to Fordham, Dr. Nagaraja was a researcher at the U.S. Census Bureau. While there, she worked on projects relating to the American Community Survey.

Contents:
Strategic Therapy. Ethnicity Issues in Strategic Therapy. Strategic Therapy with Couples. Family Therapy at a Distance - a Case of Depression. Changing a Violent Family. Compulsory Therapy - a Case of Violence. Paradox and Play with Children: The Boy Who can't stop Fighting. Mother Daughter Incest. Cultural Confusions: How Many Clients are in One Body? A Positive Approach with Psychotic Couples. Appendix A: Case Report: How to Unbalance a Couple. Appendix B: Supplemental.

One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter. Features Covers numerous statistical procedures for analyzing data based on sports results Presents fundamental methods for describing and summarizing data Describes aspects of probability theory and basic statistical concepts that are necessary to understand and deal with the randomness inherent in sports data Explains the statistical reasoning underlying the methods Illustrates the methods using real data drawn from a wide variety of sports Offers many of the datasets on the author's website, enabling you to replicate the analyses or conduct related analyses New to the Second Edition R code included for all calculations A new chapter discussing several more advanced methods, such as binary response models, random effects, multilevel models, spline methods, and principal components analysis, and more Exercises added to the end of each chapter, to enable use for courses and self-study Full solutions manual available to course instructors.

'This book represents an excellent, practical and supportive guide for those who should be engaged in mental health. It will be an invaluable tool as we work towards promoting, protecting and improving mental health in poor countries, and the incorporation of mental health issues into broader health sector and poverty reduction processes.' - Julian Lob Levyt

'This book is a major achievement, and fulfils an important need in many countries of the world.' - David Goldberg

Statistical Concepts-A Second Course presents the last 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for second and upper-level statistics courses, this book highlights how statistics work and how best to utilize them to aid students in the analysis of their own data and the interpretation of research results. In this new edition, Hahs-Vaughn and Lomax discuss sensitivity, specificity, false positive and false negative errors. Coverage of effect sizes has been expanded upon and more organizational features (to summarize key concepts) have been included. A final chapter on mediation and moderation has been added for a more complete presentation of regression models. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R. This book acts as a clear and accessible instructional tool to help readers fully understand statistical concepts and how to apply them to data. It is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral science disciplines.

As new techniques and approaches to supervision attract interest within therapy-related professions, the contributors to this informative book consider the nature of a supervision and examine the ways in which it can be further defined and developed. Drawing together practical and theoretical perspectives, Integrative Approaches to Supervision examines the contribution that supervision can make within both organisational and individual settings. The book covers frameworks and models for supervision, supervision in clinical practice and issues within integrative supervision. Topics include: different models of the supervision practice; anti-oppressive practice; spirituality and supervision; counselling supervision in health care; supervision of organisations; self-protection for supervisors from complaints and litigation. Wide in scope but rich in detail, this book is essential reading for psychotherapists, counsellors, consultants and students involved in the supervision process.

Contents:
Introduction. Chapter 1. Reinventing the Sociology of Tourism Yiorgos Apostolopoulos Section I - Towards a Sociological Understanding of Contemporary Tourism Chapter 2. Representations of International Tourism in the Social Sciences: Sun, Sex, Sights, Savings, and Servility Malcolm Crick Chapter 3. The Sociology of Tourism: Approaches, Issues, and Findings Erik Cohen Section II - The Tourism System and the Individual Chapter 4. Motivation and Anticipation in Post-Industrial Tourism Giuli Liebman Parrinello Chapter 5. A Phenomenology of Tourist Experiences Erik Cohen Section III - Structures of Social Inequality in the Tourism System Chapter 6. Tourism, Culture, and Social Inequality John Urry Chapter 7. Gender and Class Relations in Tourism Employment Michael Ireland Section IV - Tourism, Underdevelopment, and Dependency Chapter 8. Tourism, Dependency, and Development: A Mode of Analysis Stephen Britton Chapter 9. Close Encounters of the Third World Cecilia A. Karch and Graham H.S. Dann Section V - Tourism and Social Institutions Chapter 10. The Changing Economics of the Tourist Industry John Urry Chapter 11. Tourism and the Family in a Rural Cretan Community Maria Kousis Chapter 12. The Philippines: The Politicization of Tourism Linda K. Richter Section VI - Tourism and Social Change Chapter 13. Gender and Economic Interests in Tourism Prostitution: The Nature, Development, and Implications of Sex Tourism in South-East Asia C. Michael Hall Chapter 14. Interpretations of Tourism as Commodity G. Llewellyn Watson and Joseph P. Kopachevsky Section VII - Towards a 'New' Sociology of Tourism Chapter 15. Sociology and Tourism Graham Dann and Erik Cohen Chapter 16. Mega-Events and Micro-Modernization: On the Sociology of the New Urban Tourism Maurice Roche

Built around a problem solving theme, this book extends the intermediate and advanced student's expertise to more challenging situations that involve applying statistical methods to real-world problems. Data relevant to these problems are collected and analyzed to provide useful answers.
Building on its central problem-solving theme, a large number of data sets arising from real problems are contained in the text and in the exercises provided at the end of each chapter. Answers, or hints to providing answers, are provided in an appendix.
Concentrating largely on the established SPSS and the newer S-Plus statistical packages, the author provides a short, end-of-chapter section entitled "Computer Hints" that helps the student undertake the analyses reported in the chapter using these statistical packages.

Originally published in 1976, the authors of six of the most widely quoted works in behavioural science related to education, at the time, here describe in detail their research work, including its origins, planning and implementation. The accounts are unusual, not only for their technical detail but for their candour. The brief was to put the heart and brains back into accounts of research so the authors comment not only on the research design, but on the personal and professional problems they had to overcome. They also reflect on the reception of their work, and the way in which it has been adapted, misunderstood or deliberately distorted to support arguments of widely differing ideological pressure groups. The book shows how ingenuity and persistence as well as technical competence lie at the heart of the research process. The authors do not give the normal depersonalised, streamlined account which gives a false, mechanical picture of research as an occupation, but show it to be a profound personal and professional experience as they comment on the thought that lay behind their work and the way it was finally produced for publication. Dr Shipman has written a short introduction to each chapter, and contributed a concluding chapter relating the six research experiences to conventional views on the research process and to the part played by research evidence in policy making.

An overview is given of cross-cultural psychology and cultural psychology, focusing on theory and methodology. In Section 1 historical developments in research are traced; it is found that initially extensive psychological differences tend to shrink when more carefully designed studies are conducted. Section 2 addresses the conceptualization of "culture" and of "a culture". For psychological research the notion "culture" is considered too vague; more focal explanatory concepts are required. Section 3 describes methodological issues, taking the notion of the empirical cycle as a lead for both qualitative and quantitative research. Pitfalls in research design and data analysis of behavior-comparative studies, and the need for replication are discussed. Section 4 suggests to move beyond research on causal relationships and to incorporate additional questions, addressing the function and the development of behavior patterns in ontogenetic, phylogenetic and historical time. Section 5 emphasizes the need for applied research serving the global village.