On Thu, 19 Jun 2008, Bryan Hanson wrote:
Thanks so much to all who offered assistance. I have to say it would have
taken me a long time to figure this out, so I am most grateful. Plus,
studying your examples greatly improves my understanding.
As a follow up, the fit process gives the followin
Thanks so much to all who offered assistance. I have to say it would have
taken me a long time to figure this out, so I am most grateful. Plus,
studying your examples greatly improves my understanding.
As a follow up, the fit process gives the following error:
Warning messages:
1: In eval(expr,
On Thu, 2008-06-19 at 10:42 -0400, Bryan Hanson wrote:
> [I've ommitted some of the conversation so far...]
>
> > E.g. in a logistic model, with (say) eta = beta_0 + beta_1*x one may
> > find, on the
> > linear predictor scale, A and B (say) such that P(A <= eta <= B) = 0.95.
> >
> > Then P(expit
[I've ommitted some of the conversation so far...]
> E.g. in a logistic model, with (say) eta = beta_0 + beta_1*x one may
> find, on the
> linear predictor scale, A and B (say) such that P(A <= eta <= B) = 0.95.
>
> Then P(expit(A) <= expit(eta) <= expit(B)) = 0.95, which is exactly
> what is wan
On 19/06/2008, at 9:32 AM, Prof Brian Ripley wrote:
On Thu, 19 Jun 2008, Rolf Turner wrote:
On 19/06/2008, at 8:08 AM, Bryan Hanson wrote:
Hi all. I hope I have my terminology right here...
For a simple lm, one can add “pointwise confidence bounds” to a
fitted line
using something like
On Thu, 19 Jun 2008, Rolf Turner wrote:
On 19/06/2008, at 8:08 AM, Bryan Hanson wrote:
Hi all. I hope I have my terminology right here...
For a simple lm, one can add “pointwise confidence bounds” to a fitted line
using something like
predict(results.lm, newdata = something, interval = "c
On 19/06/2008, at 8:08 AM, Bryan Hanson wrote:
Hi all. I hope I have my terminology right here...
For a simple lm, one can add “pointwise confidence bounds” to a
fitted line
using something like
predict(results.lm, newdata = something, interval = "confidence")
(I'm following DAAG page
Hi all. I hope I have my terminology right here...
For a simple lm, one can add ³pointwise confidence bounds² to a fitted line
using something like
>predict(results.lm, newdata = something, interval = "confidence")
(I'm following DAAG page 154-155 for this)
I would like to do the same thing fo
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