On Oct 31, 2009, at 7:29 AM, tdm wrote:
OK, I think I've figured it out, the predict of lrm didn't seem to
pass it
through the logistic function. If I do this then the value is
similar to
that of lm. Is this by design?
Yes, at least for certain meanings of "this". When working with
p
tdm wrote:
>> OK, I think I've figured it out, the predict of lrm didn't seem to pass
>> it through the logistic
>> function. If I do this then the value is similar to that of lm. Is this
>> by design? Why would it
>> be so?
Please take some time to read the help files on these functions so th
OK, I think I've figured it out, the predict of lrm didn't seem to pass it
through the logistic function. If I do this then the value is similar to
that of lm. Is this by design? Why would it be so?
1 / (1 + Exp(-1 * 3.38)) = 0.967
tdm wrote:
>
>
> Anyway, do you know why the lrm predict g
Hi Bill,
Thanks for you comments. You may be right in that my ability to use the
software may be the problem. I was using lm to fit a model with 'target'
values of 0 or 1. I then discovered there was a lrm model as well, so just
replaced lm with lrm and expected it to be fine. Then I found that t
Hi Phil,
>> So far for logistic regression I've tried glm(MASS) and lrm (Design) and
>> found there is a big
>> difference.
Be sure that you mean what you say, that you are saying what you mean, and
that you know what you mean when making such statements, especially on this
list. glm is not in
glm is not, and never was. part of the MASS package. It's in the stats package.
Have you sorted out why there is a "big difference" between the results you get
using glm and lrm?
Are you confident it is due to the algorithms used and not your ability to use
the software?
To be helpful, if d
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