skip to main content skip to footer

Statistics and Causal Inference

Author(s):
Holland, Paul W.
Publication Year:
1985
Report Number:
RR-85-40, PSRTR-85-63
Source:
ETS Research Report
Document Type:
Report
Page Count:
72
Subject/Key Words:
Attribution Theory, Behavior Theories, Influences, Models, Philosophy, Statistical Analysis

Abstract

Problems involving causal inference have dogged 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 & 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. (76pp.)

Read More