Presenting unadjusted and adjusted estimates side by side

Steve Simon


This page is currently being updated from the earlier version of my website. Sorry that it is not yet fully available.

Someone on the Medstats discussion group asked about reporting the analysis of a model without adjustment for covariates along with the analysis adjusted for covariates. What is the purpose of reporting the unadjusted analysis?

I like to see both analyses because it lets you know whether the adjustment for covariates has had any practical impact.

Also, there is a pragmatic consideration. The unadjusted analysis represents a value that typically can be calculated by hand. In a logistic regression model comparing two groups, for example, the unadjusted odds ratio can be calculated directly from the 2 by 2 table. I like to be able to double check a few of the numbers presented in a paper just to get comfortable with the results.

Finally, the simplicity of the unadjusted estimate (if it is not seriously biased) further reinforces the credibility of the research. There’s a general perception among some cynics that if you used a complicated statistical model, it was only because the simple model did not produce results you liked. When you show that the simple model produces the same results, it takes that argument away from your critics.

You can find an earlier version of this page on my original website.