I am using inverse probability weighting to calculate stabilized weights to try to account for the loss-to-follow-up in my cohort study of children from birth to 5 years. I used multiple imputation to impute missing data for the small percentage of observations that were missing (usually <5% for each variable) to be able to calculate the stabilized weights for "DROPOUT" in the entire population.
My outcome of interest is a neurological test children not lost to follow up took at 5 years. I will be performing logistic regression models adjusted with the stabilized weights calculated from IPW. Am I supposed to include only the children with data available for the test at 5 years in my SW weighted logistic regression? Or should I have used multiple imputation to impute the missing test results and include the entire population + IPW weights?
Thank you in advance for your response