Displaying 4 results from an estimated 4 matches for "pfeffermann".
2004 May 20
1
mixed models for analyzing survey data with unequal selec tion probability
...te in a regression
model - and bytheway - the weights are the inverse of the probabilities of
selection - not the probabilities.
Fundamentally, there is a difficulty in making sense out of 'random effects'
in a finite population setting.
(plagiarized from some unknown source)
See: < 9. Pfeffermann, D. , Skinner, C. J. , Holmes, D. J. , Goldstein, H. ,
and Rasbash, J. (1998), ``Weighting for unequal selection probabilities in
multilevel models (Disc: p41-56)'', Journal of the Royal Statistical
Society, Series B, Methodological, 60 , 23-40 >
which refers back to:
<29. Pfefferma...
2004 May 07
1
sampling weights for lme
Dear All,
I have a complex survey data with observations having differing
probabilities of selection into the sample. I would like to run a
linear mixed effects model and also to use weighting that takes this
into consideration. As far as I know, however, the weighting option for
the lme command from nlme package (or glmmPQL from MASS, for that
matter) is related to heteroscedasticity. Is there a
2004 May 21
0
[Fwd: Re: mixed models for analyzing survey data with unequal selection probability]
...pling depends on a variable Z correlated with Y and X and
>you want to model the distribution of Y given X, not the distribution of Y
>given X and Z, you are still in trouble.
>
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> -thomas
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>>(plagiarized from some unknown source)
>>See: < 9. Pfeffermann, D. , Skinner, C. J. , Holmes, D. J. , Goldstein, H. ,
>>and Rasbash, J. (1998), ``Weighting for unequal selection probabilities in
>>multilevel models (Disc: p41-56)'', Journal of the Royal Statistical
>>Society, Series B, Methodological, 60 , 23-40 >
>>
>>...
2004 Aug 26
5
GLMM
I am trying to use the LME package to run a multilevel logistic model
using the following code:
------------------------------------------------------------------------
-------------------------------------------
Model1 = GLMM(WEAP ~ TSRAT2 , random = ~1 | GROUP , family = binomial,
na.action = na.omit )
------------------------------------------------------------------------