# Should we ignore covariate imbalance and stop presenting a stratified 'table one' for randomized trials?

**URL:** <https://discourse.datamethods.org/t/should-we-ignore-covariate-imbalance-and-stop-presenting-a-stratified-table-one-for-randomized-trials/547>\
**Category:** research methods\
**Tags:** reporting, rct, interpretation\
**Created:** [August 31, 2018, 1:39pm UTC](https://discourse.datamethods.org/t/should-we-ignore-covariate-imbalance-and-stop-presenting-a-stratified-table-one-for-randomized-trials/547 "2018-08-31T13:39:08Z")\
**Posts on this page:** 1\
**Showing post:** 11

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**Author:** ![f2harrell](https://discourse.datamethods.org/user_avatar/discourse.datamethods.org/f2harrell/32/165_2.png) [@f2harrell](https://discourse.datamethods.org/u/f2harrell)\
**Post date:** [August 31, 2018, 8:08pm UTC](https://discourse.datamethods.org/t/should-we-ignore-covariate-imbalance-and-stop-presenting-a-stratified-table-one-for-randomized-trials/547/11 "2018-08-31T20:08:30Z")

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The point about effect modification is important. But it’s not that ignoring this is completely wrong; more so it’s that the treatment effect will be a kind of average over levels of the interacting factor, so will not apply well to individuals even though it’s right “on the average”.

To say “randomization was inspected” is not specific enough. The randomization _process_ should be inspected and mentioned. Not covariate balance, which just reflects random occurrences.

Instead of “describe and measure prognostic factors” I’d say “pre-specify the most important prognostic factors” and adjust for them come hell or high water. This also does away with the need for your 3.

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