eveskew

# Categorical missing data in Stan

# Demonstrated with three categories

# Code and ideas adapted from @rmcelreath
# https://gist.github.com/rmcelreath/9406643583a8c99304e459e644762f82

# Code and ideas discussed with @dmontecino
# https://gist.github.com/dmontecino/b804853e4b36a57990a7108a35201cf5

AustinRochford

junpenglao

grimzy

#!/usr/bin/env bash

git branch -r | grep -v '\->' | while read remote; do git branch --track "${remote#origin/}" "$remote"; done
git fetch --all
git pull --all

aparrish

AustinRochford

aparrish

aparrish

rmcelreath

# "impute" missing binary predictor
# really just marginalizes over missingness
# imputed values produced in generated quantities

N <- 1000 # number of cases
N_miss <- 100 # number missing values
x_baserate <- 0.25 # prob x==1 in total sample
a <- 0 # intercept in y ~ N( a+b*x , 1 )
b <- 1 # slope in y ~ N( a+b*x , 1 )

mrocklin