[R] Problem with anova.lmRob() "robust" package
izahn at psych.rochester.edu
Thu Jul 28 17:52:07 CEST 2011
I found the question really confusing as well, but see below.
On Thu, Jul 28, 2011 at 11:42 AM, David Winsemius
<dwinsemius at comcast.net> wrote:
> On Jul 28, 2011, at 9:13 AM, m.fenati at libero.it wrote:
>> Dear R users,
>> I'd like to known your opinion about a problem with anova.lmRob() of
>> "Robust" package that occurs when I run a lmRob() regression on my dataset.
>> I check my univariate model by single object anova as anova(lmRob(y~x)).
>> If I compare my model with the null model (y~1), I must obtain the same
>> but not for my data.
>> Is it possible?
>> My example:
>> If I run the code omitting the factor() (then treating "x" as continuous),
>> the results are the same..
> I do not get the same results with that code. And the code does not appear
> to track your description, since the second model does not have an "x" term
> in it. Even when I create the model that it sounded as though you would have
> written, namely lmR0 <- lmRob(y ~ x), it is clearly _not_ the same result.
> (Intercept) factor(x)1 factor(x)2
> 0.2428571 -1.3432007 -0.4000000
> (Intercept) x
> -0.509524217 0.005820355
>> What is the explanation of these different results?
> Since you didn't post your results and since your complaint was that they
> are "the same", it's hard to know what you are talking about.
I think the question is why
lm1 <- lm(y ~ factor(x))
lm0 <- lm(y ~ 1)
gives the same result, but
I don't know the answer, but I think it is an interesting question.
> David Winsemius, MD
> West Hartford, CT
> R-help at r-project.org mailing list
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
University of Rochester
Department of Clinical and Social Psychology
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