<p>Definitely yes.</p>

<p>If results can be reproduced across multiple platforms, we have a <strong>methodology</strong>. If all platforms give different answers, we at best have <em>implementations</em>... and we don't know which one is the right one, if any.</p>

<p>@gung <a href="https://stats.meta.stackexchange.com/a/5210/5739">suggested</a> that the expertise required to answer questions like that needs to be statistical. Well... this is where statistics meets computation. A theoretical statistician would not be able to say why a logistic regression converges in <code>stats::glm()</code> but <code>logit</code> throws an error in Stata... <strong>hint</strong>: the likelihood is the same, but the treatment of infinite slopes and quasi-separation/perfect prediction is different. I believe statisticians would generally benefit from a greater exposure to computing issues, and that would help them understand the <em>tools</em> that they use.</p>

<p>Finally, near monopoly of R is all great for statisticians on this site to talk in common language. But hey, how many of us would be happy if your cell service were a monopoly??? I use R and Stata in my work, and SAS occasionally, and the crucial check for me that I am doing things right is when I can compare the results and see that they match.</p>
