This book provides a comprehensive multidisciplinary picture of the work on causal models. 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.
This book provides a comprehensive multidisciplinary picture of the work on causal models.
Causal models are formal theories stating the relationships between precisely defined . This classic text by Blalock addresses and resolves this concern.
Causal models are formal theories stating the relationships between precisely defined variables, and have become an indispensable tool of the social scientist. This book draws upon the best writing in a variety of fields to provide a comprehensive picture of contemporary work on this subject. There is a growing literature on causal models and structural systems of equations that crosscuts a number of different fields. However, much of this material remains widely scattered throughout the journal literature and varies considerably in terms of both level of difficulty and substantive application.
Among the frustrations constantly confronting the social scientist are those associated with the general process of measurement. The importance of good measurement has long been recognized in principle, but it has often been neglected in practice in many of the social sciences.
This book is an introduction to approaches and methodologies in the . The result is a certain ‘methodological nationalism’, which takes two forms.
This book is an introduction to approaches and methodologies in the social sciences. Approaches’ is a general term, wider than theory or methodology. There is a persistent division in the social sciences between those who prefer to break their material up into variables and those who prefer dealing with whole cases. In our experience, there are few causes of greater confusion among graduate social scientists, many of whom insist on speaking in the lan-guage of variables while working with whole cases, or occasionally vice versa.
from book Causality and Causal Modelling in the Social Sciences. This chapter presents causal models in detail. Methodology of Causal Modelling. Chapter · January 2009 with 8 Reads. How we measure 'reads'. In particular, it introduces path models, covariance structure models, Granger-causality, Rubin's model, multi level analysis, and contingency tables, by paying particular attention to the meaning of their assumptions and to their e methodology. An overview of the difficulties and weaknesses of causal models is also offered.
Hubert M. Blalock Jr. Basic Dilemmas in the Social Sciences. Understanding Social Inequality: Modeling Allocation Processes. Hubert M.
This is a companion volume to the Causal Models in the Social Sciences, the majority of articles .
This is a companion volume to the Causal Models in the Social Sciences, the majority of articles concern panel designs involving repeated measurements while a smaller cluster involves discussions of how experimental designs may be improved by more explicit attention to causal models.
Contextual-Effects Models: Theoretical and Methodological Issues. Causal Models in the Social Sciences. Andrew Bebbington, Hubert M. Blalock.
Taking an exploratory rather than a dogmatic approach to the problem, this book pulls together materials bearing on casual inference that are widely scattered in the philosophical, statistical, an. More). Contextual-Effects Models: Theoretical and Methodological Issues. Contextual-effects models represent an effort to explain individual-level de pendent variables using combinations of individualand group-level indepen dent variables. In the simplest models, th.
A Pluralist Perspective. This type of social science strives to provide answers to ‘why’ questions by seeking to identify one or several antecedent factors (explanans) that are responsible for the occurrence of the event or behaviour in question (explanandum) (Nachmias and Frankfort-Nachmias 1976). As Gerring (2005: 170) puts it: ‘to be causal, the cause in question must generate, create, or produce the supposed effect’.
This article investigates the relevance of chaos theory for social science. Blalock, H. M. (1982). Conceptualization and Measurement in the Social Sciences. Beverly Hills, CA: Sage. Bell, D. Raiffa, H. & Tversky, A. (ed. (1988). Decision Making: Descriptive, Normative, and Prescriptive Interactions. Cambridge: Cambridge University Press. Cohen, M. R. & Nagel, E. (1961). An Introduction to Logic and Scientific Method. London: Routledge & Kegan Paul.