This function combines a
wimids object columnwise with additional datasets or variables. Typically these would be variables not included in the original imputation and therefore absent in the
with() can then be used on the output to run models with the added variables.
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Objects to combine columnwise. The first should be a
An object with the same class as the first input object with the additional variables added to the components.
Farhad Pishgar and Noah Greifer
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#Loading libraries library(MatchThem) library(survey) #Loading the dataset data(osteoarthritis) #Multiply imputing the missing values imputed.datasets <- mice::mice(osteoarthritis, m = 5) #Weighting the multiply imputed datasets weighted.datasets <- weightthem(OSP ~ AGE + SEX + BMI + RAC + SMK, imputed.datasets, approach = 'within') #Adding additional variables weighted.datasets <- cbind(weighted.datasets, logAGE = log(osteoarthritis$AGE)) #Using the additional variables in an analysis models <- with(weighted.datasets, svyglm(KOA ~ OSP + logAGE, family = quasibinomial)) #Pooling results obtained from analyzing the datasets results <- pool(models) summary(results)
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