dear list members,
i would be grateful for opinion from the statistical community on an
issue i first thought trivial, but later... here it goes:
we recruited n1 = 200 patients of a disease and n2 = 380 healthy
controls to compare them in terms of some outcome using t tests.
as part of a publication process in a reputable journal which shall
remain unnamed, a reviewer complained that this setting is unbalanced;
n1 should be equal to n2.
assuming that the reviewer wants to see the principle "50-50% split
gives greatest power" upheld, we explained in a rebuttal that n1 was
limited by factors beyond our control, while n2 was not, so the choice
was either to limit n2 (and the test's power) artificially to ensure
balance or to put allocated study resources to good use and recruit more
controls and, with them, extra power and precision for our analysis.
they still, however, insist that balance is all crucial. clearly, we
cannot now (and could not have at design time) set n1 = n2 = 290. the
only way we could satisfy them would be by throwing away a random 180
extra controls and re-analyzing with n1 = n2 = 200.
my key question: could the reviewer be right on this? are there any
circumstances under which the trade-off bottom line between a
full-balance, lower power and a broken-balance, higher power approach
favors the former, if these are the only two options? if not, are there
any literature sources (or word from high-up stats experts) explicitly
clarifying this issue, something we can refer to rather than expect them
to take our word for it?
on a more general note, what is the current common wisdom on how to
handle disagreements with peer reviewers on strictly statistical issues?
i hear "the reviewer is always right" from time to time, but then find
myself feeling uncomfortable when this happens to go directly counter
even to the very basics of my med stats education.
best regards,
laszlo
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