An accessible, contemporary introduction to the methods for determining cause and effect in
the Social Sciences “Causation versus correlation has been the basis of arguments …

This paper reviews recent advances in the foundations of causal inference and introduces a
systematic methodology for defining, estimating, and testing causal claims in experimental …

David A. Freedman presents here a definitive synthesis of his approach to causal inference
in the social sciences. He explores the foundations and limitations of statistical modeling …

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 …

In this book, Reiss argues in favor of a tight fit between evidence, concept and purpose in
our causal investigations in the sciences. There is no doubt that the sciences employ a vast …

The past decade has witnessed an explosion of interest in research and education in causal
inference, due to its wide applications in biomedical research, social sciences, artificial …

In spring of 2010, Howard Kaplan invited me to compile a volume on sociological
methodology for the Springer series, Handbooks of Sociology and Social Research. I …

This article reviews recent advances in causal inference relevant to sociology. We focus on
a selective subset of contributions aligning with four broad topics: causal effect identification …

Causal inference for sociological data. Causal inference for sociological data. Citation Berk,
RA (1988). Causal inference for sociological data. In NJ Smelser (Ed.), Handbook of sociology …

Causality was at the center of the early history of structural equation models (SEMs) which
continue to serve as the most popular approach to causal analysis in the social sciences …