mixtape/R/ipw.R at master · scunning1975/mixtape · GitHub

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library(tidyverse)
library(haven)

#continuation
N <- nrow(nsw_dw_cpscontrol)
#- Manual with non-normalized weights using all data
nsw_dw_cpscontrol <- nsw_dw_cpscontrol %>%
  mutate(d1 = treat/pscore,
         d0 = (1-treat)/(1-pscore))

s1 <- sum(nsw_dw_cpscontrol$d1)
s0 <- sum(nsw_dw_cpscontrol$d0)


nsw_dw_cpscontrol <- nsw_dw_cpscontrol %>%
  mutate(y1 = treat * re78/pscore,
         y0 = (1-treat) * re78/(1-pscore),
         ht = y1 - y0)

#- Manual with normalized weights
nsw_dw_cpscontrol <- nsw_dw_cpscontrol %>%
  mutate(y1 = (treat*re78/pscore)/(s1/N),
         y0 = ((1-treat)*re78/(1-pscore))/(s0/N),
         norm = y1 - y0)

nsw_dw_cpscontrol %>%
  pull(ht) %>%
  mean()

nsw_dw_cpscontrol %>%
  pull(norm) %>%
  mean()

#-- trimming propensity score
nsw_dw_cpscontrol <- nsw_dw_cpscontrol %>%
  select(-d1, -d0, -y1, -y0, -ht, -norm) %>%
  filter(!(pscore >= 0.9)) %>%
  filter(!(pscore <= 0.1))

N <- nrow(nsw_dw_cpscontrol)

#- Manual with non-normalized weights using trimmed data
nsw_dw_cpscontrol <- nsw_dw_cpscontrol %>%
  mutate(d1 = treat/pscore,
         d0 = (1-treat)/(1-pscore))

s1 <- sum(nsw_dw_cpscontrol$d1)
s0 <- sum(nsw_dw_cpscontrol$d0)

nsw_dw_cpscontrol <- nsw_dw_cpscontrol %>%
  mutate(y1 = treat * re78/pscore,
         y0 = (1-treat) * re78/(1-pscore),
         ht = y1 - y0)

#- Manual with normalized weights with trimmed data
nsw_dw_cpscontrol <- nsw_dw_cpscontrol %>%
  mutate(y1 = (treat*re78/pscore)/(s1/N),
         y0 = ((1-treat)*re78/(1-pscore))/(s0/N),
         norm = y1 - y0)

nsw_dw_cpscontrol %>%
  pull(ht) %>%
  mean()

nsw_dw_cpscontrol %>%
  pull(norm) %>%
  mean()