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Causal Inference And Statistical Models In Modern Social Sciences

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Chapter Summary

The empirical investigation of causal relationships is an important but difficult scientific endeavor. Two different models of causal inference have dominated the work of practitioners in the social sciences over the last decades: (1) "Causation as robust dependence" and (2) "causation as consequential manipulation." The study of parallel or interdependent processes with transition rate models is one of the most important advances of event history analysis. In order to demonstrate the utility of the "causation as generative process" approach to interdependent dynamic systems, we report the results of three cross-national comparative studies about the effect of first pregnancy/first birth on entry into first marriage for couples living in consensual unions. The purpose of the earlier study by Blossfeld, Manting, and Rohwer (1993) was to gain insight into the process of how consensual unions were transformed into marriages in the former West Germany and the Netherlands.

Keywords: Blossfeld; causal inference; causation as consequential manipulation; Causation as robust dependence; Netherlands; social sciences; West Germany



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