Open AccessSTATISTICS AND CAUSAL INFERENCE *
Author(s) -
Holland Paul W.,
Glymour Clark,
Granger Clive
Publication year - 1985
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2330-8516.1985.tb00125.x
Subject(s) - causation , causal inference , inference , statistical inference , causal model , causality (physics) , psychology , epistemology , econometrics , computer science , statistics , mathematics , artificial intelligence , philosophy , physics , quantum mechanics
Problems involving causal inference have dogged at the heels of Statistics since its earliest days. Correlation does not imply causation and yet causal conclusions drawn from a carefully designed experiment are often valid. What can a statistical model say about causation? This question is addressed by using a particular model for causal inference (Rubin, 1974; Holland and Rubin, 1983) to critique the discussions of other writers on causation and causal inference. These include selected philosophers, medical researchers, statisticians, econometricians, and proponents of causal modelling.