[R] Logit / ms

[Prof Brian D Ripley]

On Sat, 23 Feb 2002, Paul Johnson wrote:

> Thanks for posting this. it is highly instructive!
>
> Can I ask follow ups? I ran this example after getting the bwt data as
> illustrated in the example for birthwt in MASS.  It runs fine and gives
> me the parameter estimates.
>
> Question 1. the estimates are a little different from the glm estimates
> obtained. The differences result from a change in optimization routines?
>   Are these small differences typical?
>
> Here are the logitreg() numbers:
>
> (Intercept)         age         lwt   raceblack   raceother   smokeTRUE
>   0.82304295 -0.03723343 -0.01565330  1.19240547  0.74067565  0.75551956
>      ptdTRUE      htTRUE      uiTRUE        ftv1       ftv2+
>   1.34374814  1.91317620  0.68020276 -0.43636831  0.17901477
>
>  > glm(low ~ . ,binomial, bwt)
>
> Call:  glm(formula = low ~ ., family = binomial, data = bwt)
>
> Coefficients:
> (Intercept)          age          lwt    raceblack    raceother    smokeTRUE
>      0.82271     -0.03722     -0.01565      1.19223      0.74051
> 0.75537
>      ptdTRUE       htTRUE       uiTRUE         ftv1        ftv2+
>      1.34365      1.91297      0.68016     -0.43633      0.17894
>
>
> Question 2. Then I wondered "how do I do significance tests on those
> estimates"?  In the glm results, I use summary(). But what of this
> logitreg? I figure just to use t tests based on the asymptotic normality
> of the b's, so I need standard errors.  To get them, it appears to me I
> go into the logitreg function, and for optim I insert Hessian=TRUE, and
> then I can torture the Hessian to get standard errors.
>
> Question 3. when logitreg prints its output, the only diagnostic
> information it gives is:
> Residual Deviance: 195.4755
>
> I'm wondering what the user is supposed to conclude from that. Isn't it
> the same as -2LL?  What benchmark do you use to say it is high or low?
> In the olden days of graduate school, they ignore that, and instead look
> for -2LLR to test that all the b's are jointly 0.
>


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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