Inferential statistics are essential for estimating likely population effects from sample data. But are they useful for comparing groups for baseline comparability?
To second Leventes nice comment, Austin et al accomplished a review of the usual practice in reporting RCTs, with interesting country-specific approaches.
https://www.researchgate.net/publication/26776077_A_substantial_and_confusing_variation_exists_in_handling_of_baseline_covariates_in_randomized_controlled_trials_a_review_of_trials_published_in_leading_medical_journals
And I find the article from Stephen Senn also helpful.
https://www.researchgate.net/publication/15200947_Testing_for_baseline_balance_in_clinical_trials
Article A substantial and confusing variation exists in handling of ...
Article Testing for Baseline Balance in Clinical Trials
Testing for baseline differences between the treatment and control group in randomized controlled trials(RCTs) is not appropriate.
Senn S. Stat Med 1994 and Roberts C BMJ 1999.
www.consort-statement.org
Any baseline differences between the groups under study are by definition due to chance (as long as the randomization was performed correctly).
Grobbee DE and Hoes AW. Randomized trials. Clinical epidemiology. Sudbury, MA: Jones and Bartlett Publishers, 2009
Intention behind test of significance
To see whether an observed difference is a real or important one.
The test actually assesses the probability (the 'P value') that the observed difference might have occurred by chance when in reality there was no difference.
Random allocation
A difference of any sort between the two groups at the time of entry to the trial will necessarily be due to chance, since randomization prevents any external influences (biases) on which subjects receive which treatment.
Putting these two ideas together, performing a significance test to compare baseline variables is to assess the probability of something having occurred by chance when we know that it did occur by chance. Such a procedure is clearly absurd.
Altman
You're all correct. It's still good to know how groups might differ,of course, but a signficance test is, as you all note, testing to see if the samples come from the same population which, of course, they do.
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