Thanks for the insight on the debugger.  It has taken me a day or so to
get use to it, but it is very helpful.

-----Original Message-----
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Ben Bolker
Sent: Tuesday, June 20, 2006 12:56 PM
To: [email protected]
Subject: Re: [R] glm beta hypothesis testing

Davis, Jacob B.  <JBDavis <at> txfb-ins.com> writes:

> 
> In summary.glm I'm trying to get a better feel for the z output.  The
> following lines can be found in the function
> 
  [snip]

  digging through the function is good: debugging your way through
the function is sometimes even better.

examples(glm,local=TRUE)  ## run glm examples and get
   ## results left in local workspace)

ls()
debug(summary.glm)
summary(glm.D93)

  shows ...
  p is object rank (~ number of parameters)
  Qr$pivot gives the order in which the parameters
have been rearranged to solve the model,
so Qr$pivot[p1] gives the rearranged order
of the coefficients.  We need this rearranged
order because we're going to extract the
unscaled covariance matrix by solving the
inverse QR matrix, which is in the pivoted
(rearranged) order.

The null hypothesis for any particular contrast
in glm is that the parameter is 0, so the
estimates of the coefficients (object$coefficients)
*are* the distance from the null hypothesis.

   Ben Bolker

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