Hi Bill, 

I get the following warning messages, one for each multiply imputed dataset:


Warning messages:

1: In eval(expr, envir, enclos) :

non-integer #successes in a binomial glm!


As you guessed, this occurs when weights are applied to a logit model in R. CEM uses weights to correctly estimate treatment effects because multiple controls could be matched to multiple treated units. See Section 2.5 here:

http://gking.harvard.edu/files/political_analysis-2011-iacus-pan_mpr013.pdf

Sorry to say I don't know anything about the error you're seeing. 

Hope that helps!

Cheers,
matt.

~~~~~~~~~~~
Matthew Blackwell
Institute for Quantitative Social Science
Department of Government
Harvard University
url: http://www.mattblackwell.org
 

2: In eval(expr, envir, enclos) :

non-integer #successes in a binomial glm!

3: In eval(expr, envir, enclos) :

non-integer #successes in a binomial glm!

4: In eval(expr, envir, enclos) :

non-integer #successes in a binomial glm!

5: In eval(expr, envir, enclos) :

non-integer #successes in a binomial glm!


My dependent variable had no missing cases, so the values for it were not imputed for any observations, and I have checked that the values of it are either 0 or 1. Any ideas why I am getting this warning? I've noticed from searching online that this warning arises when weights are included in a binomial glm model, so I wonder if it might have something to do with how cem is weighting the control observations.

(2) The second issue relates to displaying the output of the model. When I type:


> run


I get:


Logistic model on CEM matched data:

SATT point estimate: 1.509872 (p.value=0.001640)

95% conf. interval: [0.570028, 2.449717]


which is fine, but when I type:


> summary(run)


I get:


Treatment effect estimation for data:

NULL

Logistic model estimated on matched data only

Coefficients:

Error in symnum(pv, corr = FALSE, na = FALSE, cutpoints = c(0, 0.001, :

'x' must be between 0 and 1


Any idea why I'm getting this error?

Thanks for any help you can provide,
Bill


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