Presented by Dr. Perman Gochyyev: Lord’s Paradox and Consequences For Effects Of Interventions On Outcomes
The main focus of this talk is on the Lord’s paradox within the latent variable modeling framework. Lord (1967) describes a hypothetical paradox in which two researchers, analyzing the same dataset using different but defensible methods, come to very different conclusions about the effects of an intervention on outcomes. Lord’s paradox has re-emerged in many causal inference settings today around the issue of when it is appropriate to control for baseline status.