Metric Scaling: Correspondence Analysis(Quantitative Applications in the Social Sciences)

Presents a set of closely related techniques that facilitate the exploration and display of a wide variety of multivariate data, both categorical and continuous. Three methods of metric scaling, correspondence analysis, principal components analysis, and multiple dimensional preference scaling are explored in detail for strengths and weaknesses over a wide range of data types and research situations. "The introduction illustrates the methods with a small dataset. This approach is effective--in a few minutes, with no mathematical requirement, the reader can understand the capabilities, similarities, and differences of the methods. . . . Numerical examples facilitate learning. The authors use several examples with small datasets that illustrate very well the links and the differences between the methods. . . . we find this text very good and recommend it for graduate students and social science researchers, especially those who are interested in applying some of these methods and in knowing the relationship among them." --Journal of Marketing Research "Illustrate[s] the service Sage provides by making high-quality works on research methods available at modest prices. . . . The authors use several interesting examples of practical applications on data sets, ranging from contraception preferences, to pottery shards from archeological digs, to durable consumer goods from market research. These examples indicate the broad range of possible applications of the method to social science data." --Contemporary Sociology "The book is a bargain; it is clearly written." --Journal of Classification

Table of Contents:
Introduction The Basic Structure of a Data Matrix Principal Components Analysis Multidimensional Preference Scaling Correspondence Analysis of Contingency Tables Correspondence Analysis of Non-Frequency Data Ordination, Seriation, and Guttman Scaling Multiple Correspondence Analysis

About the Author :
Dr. Weller’s PhD is in Social Science and her expertise is in the area of research methods (statistics, epidemiology, and data collection). She is skilled in both qualitative and quantitative methods. She has two books on methods: Systematic Data Collection (Sage Pub) covers a wide variety of interviewing and data collection methods and Metric Scaling (Sage Pub.) covers multivariate techniques of principal components, multidimensional scaling, and correspondence analysis. For over a decade, she has been the co-director and a teacher in the National Science Foundation’s Summer Institute for Research Design. Her research interests focus on minority health issues with a focus on the measurement of beliefs. She is the co-developer of the Cultural Consensus Model (Romney, Weller, &Batchelder 1986; Romney, Batchelder, & Weller 1987; Weller 2007), a formal mathematical model for the assessment of cultural beliefs. Her research (funded by NSF) concerns the measurement of beliefs and practices among Latinos in Guatemala, Mexico, South Texas, and Connecticut. Papers include studies of Latino beliefs about AIDS/SIDA, diabetes, asthma, the common cold, and folk illnesses, as well as comparisons between community and physician beliefs on AIDS, diabetes, and the common cold. Research on diabetes also has examined the effectiveness of diabetes screening guidelines using the NHANES data (in the Proceedings of the National Academy of Sciences, Dallo& Weller 2003). She is also the co-author on the meta-analysis of condom effectiveness for sexually transmitted HIV (Davis & Weller 1999; Weller & Davis 2001) and served on the federal consensus panel to summarize research concerning condoms and sexually transmitted diseases. Current work concerns decision-making of Galveston residents when asked to evacuate for hurricane Ike. Another project is examining beliefs about the common cold and H1N1 flu in the US and Mexico. Professor Romney′s recent research has focused on human color vision ranging from cross-cultural studies of color perception to representing physical reflectance spectra in low dimensional Euclidean space (selected items available in pdf format below). Other research interests include comparative cognitive studies of semantic structures, the measurement of cultural knowledge using culture consensus theory, and multidimensional scaling. He was a Fellow at the Center for Advanced Study in the Behavioral Sciences in 1956-57. He is a Fellow of the American Academy of Arts and Sciences and a Member of the National Academy of Sciences.