On Fri, May 3, 2013 at 2:27 AM, Sebastian Weirich <
sebastian.weir...@iqb.hu-berlin.de> wrote:
> Hello,
>
> I want to specify a linear regression model in which the metric outcome is
> predicted by two factors and their interaction. glm() computes effects for
> each factor level and the levels of the interaction. In the case of
> singularities glm() displays "NA" for the corresponding coefficients.
> However, svyglm() aborts with an error message. Is there a possibility that
> svyglm() provides output for coefficients without singularities like glm()?
>
>
It's not true that svyglm() aborts with an error message whenever there are
singularities, eg
> svyglm(enroll~stype+I(stype),design=dclus1)
1 - level Cluster Sampling design
With (15) clusters.
svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc)
Call: svyglm(formula = enroll ~ stype + I(stype), design = dclus1)
Coefficients:
(Intercept) stypeH stypeM I(stype)H I(stype)M
432.9 697.4 464.9 NA NA
Degrees of Freedom: 182 Total (i.e. Null); 12 Residual
Null Deviance: 24830000
Residual Deviance: 15120000 AIC: 2599
So, perhaps you could show us what you actually did, and what actually
happened, as the posting guidelines request.
-thomas
--
Thomas Lumley
Professor of Biostatistics
University of Auckland
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