Causal Models in the Social Sciences,Used

Product Description Causal models are formal theories stating the relationships between precisely defined variables, and have become an indispensable tool of the social scientist. This collection of articles is a course book on the causal modeling approach to theory construction and data analysis. H. M. Blalock, Jr. summarizes the thencurrent developments in causal model utilization in sociology, political science, economics, and other disciplines. This book provides a comprehensive multidisciplinary picture of the work on causal models. It seeks to address the problem of measurement in the social sciences and to link theory and research through the development of causal models.Organized into five sections (Simple Recursive Models, Path Analysis, Simultaneous Equations Techniques, The Causal Approach to Measurement Error, and Other Complications), this volume contains twentyseven articles (eight of which were specially commissioned). Each section begins with an introduction explaining the concepts to be covered in the section and links them to the larger subject. It provides a general overview of the theory and application of causal modeling.Blalock argues for the development of theoretical models that can be operationalized and provide verifiable predictions. Many of the discussions of this subject that occur in other literature are too technical for most social scientists and other scholars who lack a strong background in mathematics. This book attempts to integrate a few of the less technical papers written by econometricians such as Koopmans, Wold, Strotz, and Fisher with discussions of causal approaches in the social and biological sciences. This classic text by Blalock is a valuable source of material for those interested in the issue of measurement in the social sciences and the construction of mathematical models. Review Causal models are being more widely used in the social sciences, but most of them originate in econometrics, and explanations of how to use them tend to assume a higher degree of mathematical sophistication than sociologists and political sciences seek. Contributors identified only by name set out the main models for social scientists who have an introductory knowledge of causal models and have been exposed to simple leastsquares procedures but have no training in mathematical statistics. Book News This book is important for the trend it represents as well as for its specific contents. . . . [T]he volume gives a rich picture of the history and current state (as of 1970) of causal modeling in the social sciences. The range of methodological and substantive problems covered is wide. . . . My reservations about the fifth part do not dilute my enthusiasm for this book. Arthur S. Goldberger, Journal of the American Statistical Association [Q]uite good and a continuation of Blalocks earlier (1964) work on causal models. Charles W. Mcnett, Jr., American Anthropologist [A] good and useful methodological text. A. P. M. Coxon, The British Journal of Sociology This book is a collection of articles dealing with some of the assumptions required and the issues involved in making inferences about causality from evidence consisting of correlations between data usually gathered at the same point in time. This is not a book for the novice: familiarity with the basic statistics of correlation and regression and with the conceptual issues involved in the notion of causality is assumed. . . . The quality of the material is, in all cases, high and stimulating. W. P. Irvine, Canadian Journal of Political Science [U]seful and stimulating. Neil W. Henry, Contemporary Sociology [M]ost impressive. . . . This . . . is a book about the methods of social science. J. A. Barnes, The Economic Journal This volume, consisting of a collection of papers from various disciplines, is devoted to aspects of causal model building using regressionbased systems of linear equations. . . . [T]he book is c