Sean Taylor, a PhD candidate in Information Systems at NYU’s Stern School of Business, describes the "Statistics Software Signal" and his observation that some software packages are correlated with bad science. While, I don't agree with all of his points (some fine analyses have been done with Stata, for example), I thought this was an interesting take on the R language:
When operating software doesn’t require a lot of training, users of that software are likely to be poorly trained. This is an adverse selection issue. Researchers who care about statistics enough should have gravitated toward R at some point. I also trust results produced using R, not because it is better software, but because it is difficult to learn. The software is not causing you to be a better scientist, but better scientists will be using it.
You can also read his list a of what your choice of statistical software pacakge (SAS, SPSS, Matlab, Julia and more) says about you, at the link below.
decomposition: The Statistics Software Signal
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Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).