Hi
I'm currently trying to use multiple imputation for a register based cohort analysis on maternal smoking during pregnancy and the risk of cryptorchidism and hypospadias.
My exposure smoke_cat i categorized as 0-6 + missings (4%). Category 6 is "Smoker amount unknown".
I wish to predict the missings as category 0-5 (0: Never, 1: Former, 2:<5cig/day, 3: 6-10, 4: 11-20, 5: >21). I also want to treat category 6 "Smoker, amount unknown" as missing, but to only predict it into category 2-5. How is that possible.
My current syntax is the following:
mi impute chained (ologit) smoke_cat education (regress) gestage_week birthweight (logit) parity maritalstatus (mlogit) nationality = boy_no cryptorchidism hypospadias maternalage birthyear, add(100)
Related Posts with Multiple imputations: Predicting missing for selected categories
Replace values of string variables based on a fraction of my datasetHello. I'm using a mapping table linking a question (varname) to its short label (label) in a survey…
Panel Data Help! Creating a Change VariabelHello! This is my first post and very much in need of help with a project I've been working on for s…
Panel Regression Help!!Hi all!! Firstly, thank you for reading/helping! I'm attempting a project on looking at CEO persona…
meglmHello All, I have two datasets, one with a binary outcome and the second with a count outcome. I ha…
How to estimate the trade creation and diversion effects with exporter-impoter-specific time trend?Hello guys in Statalist! I have some problems with estimation on trade creation and diversion effec…
Subscribe to:
Post Comments (Atom)
0 Response to Multiple imputations: Predicting missing for selected categories
Post a Comment