# Why is ANCOVA not appropriate for modelling post-intervention outcome, controlling for baseline

I was trying to understand the different use-cases for differences-in-differences models vs. ANCOVA (post-period = pre-period + experiment_group), for observational data. I came across the below article, which starts with:

"When comparing pretest to posttest changes in non-randomized groups, most researchers are correctly avoiding ANCOVA with posttest as the dependent variable and pretest as the covariate. "

https://www.sciencedirect.com/science/article/abs/pii/S0167876003002757

Why should that approach be avoided? I have used that approach in the past to control for regression to the mean effect, in models where we are trying to understand which behaviors and covariates are associated with different changes (improvements/worsening) in clinical outcomes.

Also, if anyone has thoughts on the DiD vs. ANCOVA for large samples, I would love to hear!

• I suspect Lord's paradox is one possible reason against the proposed model. – COOLSerdash Nov 19 '20 at 20:10
• What is “pre-period” in your regression? Is it the pre-period mean of your outcome as a covariate? – Thomas Bilach Nov 19 '20 at 20:16
• @ThomasBilach It's the measurement before the treatment/intervention (e.g. blood-pressure). post-period are the measurements after treatment. Every participants has two measurements: before and after. – COOLSerdash Nov 19 '20 at 20:27