Applied Cross Cultural Data Analysis For Social Work

Applied Cross-Cultural Data Analysis for Social Work is a research guide for examining and interpreting data for the purpose of cultural group comparisons. This book aims to provide practical applications in statistical approaches of data analyses that are commonly used in cross-cultural research and evaluation. Readers are presented with step-by-step illustrations in the use of descriptive, bivariate, and multivariate statistics to compare cross-cultural population using large-scale, population-based survey data. These techniques have important applications in health, mental health, and social science research relevant to social work and other helping professions, especially in providing a framework of evidence to examine health disparities using population-health data. For each statistical approach discussed in this book, Thanh V. Tran and Keith T. Chan explain the underlying purpose, basic assumptions, types of variables, application of the Stata statistical package, the presentation of statistical findings, and the interpretation of results. Unlike previous guides on statistical approaches and data analysis in social work, this book explains and demonstrates the strategies of cross-cultural data analysis using descriptive and bivariate analysis, multiple regression, additive and multiplicative interaction, mediation, SEM and HLM for subgroup analysis and cross-cultural comparisons. This book also includes sample syntax from Stata for social work researchers to conduct cross-cultural analysis with their own research.

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. A website features 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 book is divided into techniques for analyzing cross-cultural data within the generalized-latent-variable approach: multiple-group confirmatory factor analysis and multiple-group structural equation modeling; multi-level analysis; latent class analysis; and item-response theory. Since researchers from various disciplines often use different methodological approaches, a consistent framework for describing and applying each method is used so as to cross ‘methodological borders’ between disciplines. Some chapters describe the basic strategy and how it relates to other techniques presented in the book, others apply the techniques and address specific research questions, and a few combine the two. A table in the preface highlights for each chapter: a description of the contents, the statistical methods used, the goal(s) of the analysis, and the data set employed. 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.

This is an integrated introduction to methods, research design, and data analysis tailored to the challenges of cross-cultural research.

Earlier edition published as: Developing cross-cultural measurement.

In this volume, progressive experts survey recent trends in qualitative study, which relies on small sample groups and interview data to better represent the context and complexity of social work practice. Chapters address different approaches to qualitative inquiry, applications to essential areas of research and practice, integration of qualitative and quantitative methods, and epistemological issues. This second edition brings even greater depth and relevance to social work qualitative research, including new material that tackles traditional research concerns, such as data quality, ethics, and epistemological stances, and updated techniques in data collection and analysis. To increase the usefulness for students and researchers, the editors have reorganized the text to present basic principles first and then their applications, and they have increased their focus on ethics, values, and theory. New and revised illustrative studies highlight more than ever the connection between effective research and improved social functioning among individuals and groups. The collection continues to feature scholars and practitioners who have shaped the social work research practice canon for more than twenty years, while also adding the innovative work of up-and-coming talent.

Research Methods & Data Analysis for Multicultural Social Work and Human Services introduces research methodology to social work students and practitioners. It provides hands-on examples of how to conduct data analysis in SPSS and Stata. It equips readers with the skills needed to become critical research consumers and to engage in agency-based research and evaluation. The text teaches students how to collect appropriate data and analyze data that is suitable for each type of research design. It prepares them to conduct applied social science research in a variety of fields, such as health and mental health, ethnic studies, acculturation, family violence, LGBT studies, and more. Topics addressed include the process of research, ethical issues, the validity and reliability of research instruments, design types, and relevant statistical tools. Research Methods & Data Analysis for Multicultural Social Work and Human Services provides a solid foundation and knowledge base for students and researchers. It is an excellent resource for undergraduate and graduate level research methods and design classes and courses on research and statistics in social work. Thanh V. Tran holds a Ph.D. and a master of science degree in social work from the School of Social Work at the University of Texas, Arlington. Dr. Tran is a professor in the Boston College School of Social Work in Chestnut Hill, Massachusetts. Ce Shen earned a Ph.D. in sociology at Boston College in Chestnut Hill and is now an associate professor in the college's School of Social Work. Siyon Rhee earned a Ph.D. at the School of Social Welfare, University of California, Los Angeles. Dr. Rhee teaches in the School of Social Work at California State University, Los Angeles.

Developing Cross-Cultural Measurement in Social Work Research and Evaluation, Second Edition is an applied practice-to-research text, with a focus on developing, assessing, and validating meaningful measurements across cultures and populations. This book deeply examines cultural differences that may present problems with measurements for target populations relevant to social work researchers, and features practical hands-on solutions to managing these problems using advanced quantitative methods. The authors present a step-by step approach, beginning with the conceptualization of measurements for different cultures, the processes involved in identifying item questions, and the quantitative techniques that can be used to validate new or pre-existing measures. This Second Edition also includes sample syntax from publicly available data for social work researchers to learn to conduct these types of analyses with their own research. New to the Second Edition: - Emphasis on Item Response Theory, and a new chapter devoted to the concept. - Increased focus on the process of instrument development, based on real-world examples - in particular, a detailed examination of the development of a new cross-cultural instrument, the Empathy Scale, created and validated by a group of multinational and culturally diverse students from the US, China, Mexico, and Turkey under the supervision of Dr. Tran. - Significant updates of all content to reflect new developments in cross-cultural research across social sciences and psychological disciplines.

In this book, top specialists address theoretical, methodological, and empirical multilevel models as they relate to the analysis of individual and cultural data. Divided into four parts, the book opens with the basic conceptual and theoretical issues in multilevel research, including the fallacies of such research. Part II describes the methodological aspects of multilevel research, including data-analytic and structural equation modeling techniques. Applications and models from various research areas including control, values, organizational behavior, social beliefs, well-being, personality, response styles, school performance, family, and acculturation, are explored in Part III. This section also deals with validity issues in aggregation models. The book concludes with an overview of the kinds of questions addressed in multilevel models and highlights the theoretical and methodological issues yet to be explored. This book is intended for researchers and advanced students in psychology, sociology, social work, marriage and family therapy, public health, anthropology, education, economics, political science, and cultural and ethnic studies who study the relationship between behavior and culture.