These two threads seem closely related:
What are alternatives to p-values - an earlier thread, which originally was asked from quite a "software implementation in R" point of view, but received a rather more general response.
ASA discusses limitations of p-values - what are the alternatives? - a more recent thread, written in response to the recent ASA report on p-values and statistical significance, which is perhaps a bit more wider ranging, but whose answers bear some similarity to the earlier question.
Because they quote different stimulus material which the answers responded to, it wouldn't be possible to merge the two threads - answers to one question would not fit as answers to the other. But it is hard to see that the two threads are sufficiently distinct to justify both remaining open.
I'm minded to suggest the former thread should be closed as a duplicate - there is some incongruity between the OP's search for "how to do something other than p-values in R" and the type of answers that it received, which seems a bit of a weakness. The second question is completely software agnostic and has a better focus on statistical issues, and arguably it's an advantage that it is more on top of current issues e.g. the ASA report (though being "topical" can arguably be a disadvantage as well, because it means the thread might "date" less well as academic discussion moves on beyond the ASA report).