sghi

As someone who uses and teaches R extensively (and loves the tidyverse) the tidyverse is so much easier to teach to people without any programming experience and who have very little faith in their tech or maths skills (which was me as well).

The tidyverse just 'made sense' to me when I started using R for the first time a few years ago, and now I love using R and programming. On the other hand, some of my ex-classmates learnt base R (because that's what we were taught) and found it hard, didn't learn anything properly, and now still think R or other programming languages are opaque and hard.

I'm not particularly fussed if Statistics Profs prefer data.table to dplyr or base R to tidyr, I know what is easier to teach, understand and use for me and a lot of other ecology/bio students and people.

I'd always (and always do) google an advert rather than trying to remember the exact website anyway. If you search 'href sep' or 'hrefs seo' or even 'aref seo' it always still comes up as the first result for me.

So this is the research area that I currently work in, albeit with a disease ecology perspective rather than a biochemistry one. I've had a quick read of it and and although it does seem to track other research that has been done ("Why are behavioral and immune traits linked?" by Lopes 2017 is a nice review) I'd love to see some power analyses - the sample size seems pretty small for something as complex as this question. The study I'm helping with now has a minimum sample size in the hundreds, for instance, for a broadly similar question. PCA-ing a few tests together is pretty common, but also comes with a lot of potential biases (see "Avoiding the misuse of BLUP in behavioural ecology" by Houslay and Wilson if anyone is interested!)

Are you sure? I'm nearly certain that PLOS is a publisher that charges manuscript charges for OA papers - most do.

I'm pretty sure they would be able to - I worked with cancer trial data (just a student job, doing data entry) but all patients were completely anonymised to anyone working with the data but readily identifiable by a specific unique ID number, so higher-level trial managers and doctors could find patient information if needed.