Theory-Based Data Analysis for the Social Sciences
Format:Paperback
Publisher:SAGE Publications Inc
Published:5th Feb '13
Currently unavailable, and unfortunately no date known when it will be back
This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
“In clear and accessible prose, this book presents a compelling logic for the analysis of non-experimental data. In the process, it clarifies the concepts of statistical association, confounding, and statistical control, and it provides really compelling elaboration schemes to make substantive, rather than purely statistical, sense of it all. It also provides a means for making causal assertions when the criteria of association, causal priority, non-spuriousness, and theoretical rationale are met.” -- Robert Bickel
“This text does a superb job of explaining critical concepts such as mediation, moderation, spuriousness, and control variable, using graphic illustrations as well as published articles as examples. I think the illustrated examples are really helpful for illuminating these concepts. Furthermore, the majority of empirical research in the social behavioral sciences utilizes regression, logistic regression, and path analysis. The book discusses many empirical articles utilizing these analytic approaches as examples. Thus, the contents of this book are highly relevant and understandable for those in early stages of research training.” -- Eun Young Mun
I think this is a very much awaited book. I think it is very well suited for PG level, particularly for those MA students who are writing their dissertations (and PhD students as well). As strange as it may seem, students struggle to understand what theory is and how it relates to data. For me this book engages comprehensively in these questions. There is a good discussion of how to work with variables, about the construction of associations and causalities. I wish I could teach more of this book in my MA course, but due to time constraints I would definitely recommend Chapter 1-4 (where the focus is on conceptual discussion). The book is very helpful for those constructing and designing their research. The book is not the ‘beginner level’. It would be helpful if students already have some background in quantitative analysis, therefore I would not, however, recommend for BA level. -- Maria Karepova
ISBN: 9781412994354
Dimensions: unknown
Weight: 840g
472 pages
2nd Revised edition