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.

The first comprehensive and statistically significant analysis of the predictive powers of each cross-cultural model, based on nation-level variables from a range of large-scale database sources such as the World Values Survey, the Pew Research Center, the World Bank, the World Health Organization, the UN Statistics Division, UNDP, the UN Office on Drugs and Crime, TIMSS, OECD PISA. Tables with scores for all culture-level dimensions in all major cross-cultural analyses (involving 20 countries or more) that have been published so far in academic journals or books. The book will be an invaluable resource to masters and PhD students taking advanced courses in cross-cultural research and analysis in Management, Psychology, Sociology, Anthropology, and related programs. It will also be a must-have reference for academics studying cross-cultural dimensions and differences across the social and behavioral sciences.

With internationalization, the world is becoming smaller and the opportunity to meet people from other countries and cultures is becoming more common, providing the need for cooperation, shared knowledge, and cross-border trade. Individual cultures tend to understand themselves best and base their understanding of the world and its peoples on ideas they each have come to believe irrespective of reality, and thus make it difficult to reach a proper understanding of other cultures. This book considers intercultural understanding and co-action, partly by means of general insights into the concept of culture and the dimensions which bring about cultural differences, and partly as a methodology to analyze a certain culture - whether one's own or others'. This leads towards an understanding of cultural complexity and cultural differences among people. The book provides a discussion of a number of ethical issues, which almost invariably will arise when people meet and co-act across cultural boundaries. Cultural Analysis offers a theoretical/abstract proposal for cultural understanding, intercultural plurality, and complexity.

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

`A sound guide through the complexities of cross-cultural research, written by an international team of first-rate scholars' - Harry C Triandis, University of Illinois This comprehensive guide, which covers all major issues in the field, presents cross-cultural methodology in a practical light. The initial presentation of theory serves as a basis for the discussion of methods, design and analysis that follows. Topics examined include: the design and analysis of quasi-experiments - the dominant framework for cross-cultural research; the most important tools of cross-cultural research; and the most useful techniques, illustrated with sample data.

This unique monograph provides a theoretical and methodological account on how to do cross-cultural genre analysis with the aids of corpus tools. Cross-cultural genre analysis investigates how discourse communities from different cultural backgrounds use language to realize a particular genre. It can shed light on genre nature as well as cultural specificities. The book suggests five specific approaches in doing cross-cultural genre analysis: Investigating genre context; Approaching genre complexity; Exploring genre nature; Exploring culture specificity; and Focusing on specific communicative functions. Each of these approaches is illustrated and demonstrated in a specific chapter with practical analyses of the genre of CSR reports. Covering linguistic analysis of CSR reports in three languages: Chinese, English and Italian, Yu provides insights into implications for both genre theories and CSR communication practice. By applying the cross-cultural perspective in corporate discourse analysis, her book demonstrates how the approach of cross-cultural genre analysis is fruitful and valuable in providing practical insights into the textual practice of CSR reporting in a globalized context. Moreover, in the final parts of the book, Yu illustrates how cross-cultural genre analysis can be applied in the didactic field of writing, translation and cross-cultural studies. This volume is a valuable reference to scholars of genre analysis, corpus-based studies, cross-cultural studies and corporate communication. Moreover, it is also useful for professionals involved in compiling CSR reports. Armed with the knowledge imparted in this book, the reader should be able to analyze other genres from a cross-cultural perspective. In particular, instructions on how to use specific corpus tools are provided in the appendices, which can give scholars basic technical knowledge to approach the field of cross-cultural genre analysis.

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.