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    $\begingroup$ Please provide more details on the Cox model that you used. With a dichotomous predictor like sex one typically only has a single "main"-effect coefficient and a single "interaction" effect with a treatment. Without seeing the model as written, it's hard to know how to interpret the separate A*sex=Female and A*sex=Male coefficients. Please provide that information by editing the question, as comments are easy to overlook and can be deleted. $\endgroup$ Commented Jan 9, 2023 at 14:34
  • $\begingroup$ @EdM done, I have added more details are requested, hopefully my question is now understandable $\endgroup$ Commented Jan 9, 2023 at 15:18
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    $\begingroup$ Your calculation of the A*sex=Female coefficient is based on the sum of the A:sexFemale and the A coefficients. In estimating the CI, did you take into account the covariance between those coefficients or just use their individual standard errors? Please edit the question to show those details. You might still get a "statistically insignificant" result but it's important to start with knowing whether the CI were calculated properly. $\endgroup$ Commented Jan 9, 2023 at 16:31
  • $\begingroup$ Yes, it was. I am rather interested in the interpretation of such results from a general point of view rather than in the specific scenario, as this (non-statistically significant interaction with different statistical significance in the two groups) is one common situation, so that would be particularly interesting $\endgroup$ Commented Jan 9, 2023 at 16:45
  • $\begingroup$ "However, how can one interpret the non-statistically significant results observed for females, while the effect remained statistically significant in males? " What does this mean? How do you differentiate between 'for males' and 'for females'? $\endgroup$ Commented Jan 13, 2023 at 22:35