[R] glm(weights) and standard errors
Steve Taylor
steve.taylor at aut.ac.nz
Thu May 24 03:49:24 CEST 2012
Re:
coef(summary(glm(extra ~ group, data=sleep[ rep(1:nrow(sleep), 10L), ] )))
Your (corrected) suggestion is the same as one of mine, and doesn't do what I'm looking for.
-----Original Message-----
From: David Winsemius [mailto:dwinsemius at comcast.net]
Sent: Tuesday, 22 May 2012 3:37p
To: Steve Taylor
Cc: r-help at r-project.org
Subject: Re: [R] glm(weights) and standard errors
On May 21, 2012, at 10:58 PM, Steve Taylor wrote:
> Is there a way to tell glm() that rows in the data represent a certain
> number of observations other than one? Perhaps even fractional
> values?
>
> Using the weights argument has no effect on the standard errors.
> Compare the following; is there a way to get the first and last models
> to produce the same results?
>
> data(sleep)
> coef(summary(glm(extra ~ group, data=sleep))) coef(summary(glm(extra ~
> group, data=sleep,
> weights=rep(10L,nrow(sleep)))))
Here's a reasonably simple way to do it:
coef(summary(glm(extra ~ group, data=sleep[ rep(10L,nrow(sleep)), ] )))
--
David.
> sleep10 = sleep[rep(1:nrow(sleep),10),] coef(summary(glm(extra ~
> group, data=sleep10))) coef(summary(glm(extra ~ group, data=sleep10,
> weights=rep(0.1,nrow(sleep10)))))
>
> My reason for asking is so that I can fit a model to a stacked
> multiple imputation data set, as suggested by:
>
> Wood, A. M., White, I. R. and Royston, P. (2008), How should variable
> selection be performed with multiply imputed data?.
> Statist. Med., 27: 3227-3246. doi: 10.1002/sim.3177
>
> Other suggestions would be most welcome.
>
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