#Loading libraries
library(survey)
#Loading the dataset
data(osteoarthritis)
#Multiply imputing the missing values
imputed.datasets <- mice::mice(osteoarthritis, m = 5)
#Estimating weights of observations in the multiply imputed datasets
weighted.datasets <- weightthem(OSP ~ AGE + SEX + BMI + RAC + SMK,
imputed.datasets,
approach = 'within',
method = 'glm',
estimand = "ATT")
#Analyzing the weighted datasets
models <- with(data = weighted.datasets,
exp = svyglm(KOA ~ OSP, family = binomial))
#Pooling results obtained from analysing the datasets
results <- pool(models)
#Checking the 'results' object
is.mimipo(results)
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