Earlier edition published as: Developing cross-cultural measurement.

Social workers engage in cross-cultural research in order to understand how diverse populations cope with life situations, to identify risk and protective factors across cultures, and to evaluate the effectiveness of policies and programs on the well-being of individuals from different cultures. In order to do so, it is necessary to begin with meaningful, appropriate, and practical research instruments, yet such instruments are not always readily available, or they may be misleading or biased. In this clearly written pocket guide, social work researchers will find a concise, easy-to-follow explanation of how to develop and assess cross-cultural measures that sidestep such complications and provide reliable, valid data. Using a step-by-step approach, expert cross-cultural researcher Thanh V. Tran carefully explores the issues and methodology in cross-cultural measurement development in social work research and evaluation. The book draws on existing cross-cultural research in social sciences and related areas to illustrate how to formulate research questions, select observable statistics, understand cross-cultural translation, evaluate and implement measurement equivalence, and discern quality within practices of measurement development. Tran also discusses how to use statistics software programs such as SPSS to generate data for LISREL analyses, providing enough detail to help readers grasp the programs' applications in this area but not so much as to overwhelm. This concise text offers a wealth of knowledge about using and interpreting the use of culturally relevant research instruments. Doctoral students and social researchers in the field seeking guidance in selecting and adapting such instruments in their studies, or developing and assessing their own, will find it a terrific source of essential information for their work. For additional resources, visit http://www.oup.com/us/pocketguides.

Social workers engage in cross-cultural research in order to understand how diverse populations cope with life situations, to identify risk and protective factors across cultures, and to evaluate the effectiveness of policies and programs on the well-being of individuals from different cultures. In order to do so, it is necessary to begin with meaningful, appropriate, and practical research instruments, yet such instruments are not always readily available, or they may be misleading or biased. In this clearly written pocket guide, social work researchers will find a concise, easy-to-follow explanation of how to develop and assess cross-cultural measures that sidestep such complications and provide reliable, valid data. Using a step-by-step approach, expert cross-cultural researcher Thanh V. Tran carefully explores the issues and methodology in cross-cultural measurement development in social work research and evaluation. The book draws on existing cross-cultural research in social sciences and related areas to illustrate how to formulate research questions, select observable statistics, understand cross-cultural translation, evaluate and implement measurement equivalence, and discern quality within practices of measurement development. Tran also discusses how to use statistics software programs such as SPSS to generate data for LISREL analyses, providing enough detail to help readers grasp the programs' applications in this area but not so much as to overwhelm. This concise text offers a wealth of knowledge about using and interpreting the use of culturally relevant research instruments. Doctoral students and social researchers in the field seeking guidance in selecting and adapting such instruments in their studies, or developing and assessing their own, will find it a terrific source of essential information for their work. For additional resources, visit http://www.oup.com/us/pocketguides.

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.

"This practical "how to" guide integrates a comprehensive, interdisciplinary review of literature, and a wealth of the authors' combined research experience into a framework for behavioral health and other investigators to successfully plan, budget, assess, engage in, analyze, and report participant recruitment and retention in intervention and evaluation research studies"--

Introduction to nonparametrics -- Analyzing single variables and single groups -- Comparing two or more independent groups -- Comparing two or more related groups -- Predicting with multiple independent variables -- Appendix -- Index

Over thirty years of input from instructors and students have gone into this popular research methods text, resulting in a refined ninth edition that is easier to read, understand, and apply than ever before. Using unintimidating language and real-world examples, it introduces students to the key concepts of evidence-based practice that they will use throughout their professional careers. It emphasizes both quantitative and qualitative approaches to research, data collection methods, and data analysis, providing students with the tools they need to become evidence-based practitioners.