On Fri, May 3, 2013 at 2:27 AM, Sebastian Weirich <
sebastian.weirich@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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