Dear Steve,

Since this relates as well to the message I posted a couple of minutes before 
yours, I agree that it’s possible to phrase “best practices” too categorically. 
In the current case, I believe that it’s reasonable to say that specifying the 
data argument is “generally” or “usually” the best option. That doesn’t rule 
out exceptions.

Best,
 John

  -------------------------------------------------
  John Fox, Professor Emeritus
  McMaster University
  Hamilton, Ontario, Canada
  Web: http::/socserv.mcmaster.ca/jfox

> On Dec 17, 2018, at 7:49 AM, S Ellison <s.elli...@lgcgroup.com> wrote:
> 
> 
> 
>> From: Thomas Yee [mailto:t....@auckland.ac.nz]
>> 
>> Thanks for the discussion. I do feel quite strongly that
>> the variables should always be a part of a data frame. 
> 
> This seems pretty much a decision for R core, and I think it's useful to have 
> raised the issue.
> 
> But I, er, feel strongly that strong feelings and 'always' are unsafe in a 
> best practice argument. 
> 
> First, other folk with different use-cases or work practice may see 'best 
> practice' quite differently. So I would pretty much always expect exceptions.
> 
> Second, for examples of capability, there are too many exceptions in this 
> instance. For example:
> glm() can take a two-column matrix as a single response variable. 
> lm() can take a matrix as a response variable. 
> lm() can take a complete data frame as a predictor (see ?stackloss)
> 
> None of these work naturally if everything is in a data frame, and some won’t 
> work at all.
> 
> Steve E
> 
> 
> 
> 
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