I am examining how sex affects the relationship between 2 variables. So, my model looks like: $$ y \sim sex * x $$ However, there is a known effect of menstrual cycle on $y$ (obviously in females only). Is there a way that I could include this as a covariate in the analysis, while still keeping both groups?

Let's say in females I have factor $m$ that is either 0 (follicular phase) or 1 (luteal phase), representing where they are in their cycle. Would my model be as simple as: $$ y \sim m + sex * x $$ where I would code all men as 0 for the covariate $m$?

Would it matter if the covariate was continuous?

  • $\begingroup$ I'd try recoding sex as a 3 level variable $\endgroup$ – thomaskeefe May 13 at 0:36
  • $\begingroup$ @thomaskeefe I thought about that. Then would have to construct contrasts for the 'interesting' hypotheses (i.e. not interested if the 2 female groups differ) $\endgroup$ – tomr May 13 at 18:53
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    $\begingroup$ @kjetilbhalvorsen I think that does. The comments alluded to a continuous case, but got a little muddy for me. Regardless, at this point that is not my issue. Thanks, would never have guessed from that title of that post that it would address my question. $\endgroup$ – tomr May 13 at 18:54