[R] Significance level for glm.cluster

[Lorenz, Jennifer]

Hi everyone,

I have a question with reference to "glm.cluster" from the package "miceadds" and hope that someone can help me. I am trying to calculate cluster-robust standard errors for a glm-model with multiply imputed datasets. Everything works just fine with glm.cluster but in the end I just get an output with estimates, standard errors and confidence intervals. But I need to report the significance level and I cannot figure out how to obtain this.
Here is the code I ran:

mod <- lapply(impulist, FUN=function(imp1){
  glm.cluster(data=imp1, formula=AV ~ p123 + ISEI, family=binomial("logit"), cluster=imp1$ID_s)
})
# extract parameters and covariance matrix
betas <- lapply( mod , FUN = function(rr){ coef(rr) } )
vars <- lapply( mod , FUN = function(rr){ vcov(rr) } )
# conduct statistical inference
summary( mitools::MIcombine(betas,vars) )

And that's what the output looks like:


Multiple imputation results:

      MIcombine.default(betas, vars)

                  results           se        (lower        upper) missInfo

(Intercept) -2.785309e+00 1.344773e-01 -3.053180e+00 -2.5174383210     25 %

P123         8.273687e-05 2.834233e-05  1.797328e-05  0.0001475005     74 %

ISEI         3.788065e-02 2.347762e-03  3.270191e-02  0.0430593934     67 %

Thanks for your help!
Best,
Jen


---
Jennifer Lorenz, M.A.
Georg-August-Universität Göttingen
Sozialwissenschaftliche Fakultät
Institut für Erziehungswissenschaft
Lehrstuhl Schulpädagogik / Empirische Schulforschung

e-mail: jlorenz at uni-goettingen.de<mailto:jlorenz at uni-goettingen.de>
phone: 0551-39-21411
adress: Waldweg 26, 37073 Göttingen
room: 8.106


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