Relevant literature

[llrs]

Check this paper: Batch Effect Confounding Leads to Strong Bias in Performance Estimates Obtained by Cross-Validation (PMC4072626) that measures how bad batch effects are. Perhaps the same simulations could be used to show how to avoid them. code

The bias in the cross-validation performance estimates is not eliminated by the batch effect removal, and consequently the cross-validation performance estimates obtained after batch effect elimination are not more reliable measures of the true performance than those obtained without batch effect elimination.

[llrs]

Another relevant manuscript: https://projecteuclid.org/journals/bayesian-analysis/advance-publication/Bayesian-Experimental-Design-Without-Posterior-Calculations-An-Adversarial-Approach/10.1214/22-BA1306.full

With relevant code here (not a package) and in python most of it