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I've created 12 imputed samples using the MICE package and wish to run paired sample t-tests and cohen's d calculation using an imputed dataset but I'm not sure how to do this. My end goal is to compare parameter estimates, t-test results and effect size estimates from both complete case analysis and adjusted (via MICE) to compare these, but while I have no issue with parameter estimates, I can't figure out t-tests and cohen's d.

I'm a bit confused as to how to approach this and searching online and in the mice package documentation and has not led to much progress. I did find mi.t.test from the MKmisc package but this appears to be for datasets imputed using Amelia, not MICE, and I can't quite figure it out. Would anyone have any advice or resources here please?

So far I have:

  1. Identified auxiliary variables
  2. Created Predictor Matrix
  3. Imputed missing data m times
  4. Fit & pooled estimates for linear models using with() for parameter estimates using summary()

Is there perhaps a way I can create an object of an imputed dataset that is usable with other analyses or am I looking at this in the wrong way?

Seafra Barrett
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1 Answers1

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I used multiple imputations for the first time for my research, but maybe I can help you by passing on the tips I received.

  • Perform the t-test on every imputed dataset
  • Use the Mice pool.scalar function. You can find documentation online. For Q fill in the Mean Difference, and for U the Standard Error Difference.
  • Then your pooled t-value is: qbar / sqrt(t) You can find the values of qbar and t in the output of pool.scalar
  • And your pooled p-value is: 2 * (1 - pt(abs(statistic), pmax(DF, 0.001)))

Hope this helps!

Daisy
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