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Completed data sets were obtained from 20 patients.
Once all measurements and Wolbachia screens were completed, data sets were combined and analyzed for differences among treatments.
This is done m times, generating m completed data sets.
This method "fills in" plausible values for the missing data, creating five imputed (completed) data sets.
All statistical analyses of the patient outcome data are based upon the 61 completed data sets.
The missing genotypes are imputed many times, leading to many completed data sets.
Similar(22)
A sensitivity analysis on the completed data set for these five factors showed quantitatively similar results.
Our HMI produced m = 10 complete data sets.
This step results in a number of complete data sets.
Analysis: The various complete data sets formed are analyzed.
Multiple imputation inference procedures are applied to the resulting multiply imputed complete data sets.
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