In this paper:
Lurking Variables: Some Examples Brian L. Joiner The American Statistician Vol. 35, No. 4, Nov., 1981 227-233
Brian Joiner claims that "randomization is not a panacea". This is contrary to common statements such as the one below:
A well-designed experiment includes design features that allow researchers to eliminate extraneous variables as an explanation for the observed relationship between the independent variable(s) and the dependent variable. These extraneous variables are called lurking variables.
The quote was taken from this question and does not have a source but in my experience it is representative of the prevailing attitude: Examples of Lurking Variable and Influential Observation
One example given is that when testing the safety (specifically carcinogenesis) of red #40 food dye on rodents in the seventies an effect of cage position was found to confound the study. Now I have read many journal articles studying carcinogenesis in rodents and have never seen anyone report controlling for this effect.
Further discussion of these studies can be found here: A case study of statistics in the regulatory process: the FD&C Red No. 40 experiments.
I could not find a non-paywalled version but here is an excerpt:
At the January meeting, we presented a preliminary analysis (14) that disclosed a strong correlation between cage row and RE (reticulo-endothelial tumor) death rates, which varied from 17% (bottom row) to 32% (top row) (table 2). We could not explain this strong association by sex, dosage group, or rack column or position. A subsequent analysis (18) also indicated that cage position (front vs. back) might be correlated with non-RE mortality and that position was correlated with time to non-RE death.
I am specifically interested in why there seems to be such a problem with replication in the medical literature, but examples from all fields would be welcome. Note that I am interested in examples from randomized controlled experiments, not observational studies.