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This book takes the reader through all the phases of designing and implementing group work research - that is, formulating a research question, developing hypotheses, selecting instruments, and disseminating.

This pocket guide provides a comprehensive start-to-finish overview of the basics of scale development, giving practical guidance that practitioners at all levels will be able to put to use.

Adopting ethnography as a meta-framework for social work research, this pocket guide provides a detailed, step-by-step approach for integrating cultural components and cultural awareness into the research process.

This pocket guide introduces readers to linear regression analysis, analysis of variance and covariance, and path analysis with an emphasis on the basic statistics. It prepares doctoral students and early career social work researchers with limited statistics exposure in the use of multivariate methods by providing an easy-to-understand presentation.

This practical "how to" guide integrates a comprehensive, interdisciplinary review of literature, alongside 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.

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-culturalpopulation 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 usingpopulation-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 andbivariate 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.