This is some sort of NCES data, right?

I can't see any way to get that particular error (which happens inside
glm.fit()) for a logistic model.
  Are there any negative or missing weights?
  What do you mean 'represented by blank cells' -- you can't have blank
cells in a data.frame object?
  What does traceback() give after the error?
  What is the model?

   -thomas



On Mon, Feb 10, 2014 at 4:10 PM, Claire Wladis <cwladis@gmail.com> wrote:

> Hello,
> I am using the survey package for the first time to analyze a dataset that
> has both weights and 200 BRR replication weights.  When I try to run svyglm
> on the output from svrepdesign, I get an error message that I do not know
> how to interpret, and an extended period of time searching for this error
> on the web hasn't returned any results that seem relevant to my situation.
>  I have no idea how to proceed with my analysis at this point, so I am
> hoping that someone with more experience with this package and with R in
> general would be willing to help me figure out what the problem is.
>
> Here is my code:
> surveydatastructure <- svrepdesign(repweights=dataset[, 29:228] ,
> data=dataset, weights=dataset$WTA000)
>
> modeloutput <- svyglm(model, design=surveydatastructure,
> family=quasibinomial() )
>
> The model is defined in an earlier line of code, but for the sake of
> readability here, I have not included it.  The dataset has a binary
> dependent variable and a combination of categorical and continuous
> variables as dependent variables.  There is missing data in the dataset,
> represented by blank "cells" in the data frame.  The data itself is
> restricted but I can describe any part of it as necessary.
>
>
> Here is the error message that R returns when I enter the svyglm function
> line of code:
>
> Error in if (!(validmu(mu) && valideta(eta))) stop("cannot find valid
> starting values: please specify some",  :  missing value where TRUE/FALSE
> needed
>
> Thanks for reading my post, and thanks in advance for any help!
> Sincerely,
> Claire
>
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>
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>



-- 
Thomas Lumley
Professor of Biostatistics
University of Auckland

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