6 Bootstrapping
library(PSAboot)
boot.matching.1to3 <- function(Tr, Y, X, X.trans, formu, ...) {
return(boot.matching(Tr=Tr, Y=Y, X=X, X.trans=X.trans, formu=formu, M=3, ...))
}
boot_out <- PSAboot(Tr = lalonde$treat == 1,
Y = lalonde$re78,
X = lalonde[,all.vars(lalonde.formu)[-1]],
seed = 2112,
methods=c('Stratification' = boot.strata,
'ctree' = boot.ctree,
'rpart' = boot.rpart,
'Matching' = boot.matching,
'Matching-1-to-3' = boot.matching.1to3,
'MatchIt' = boot.matchit) )
summary(boot_out)## Stratification Results:
## Complete estimate = 1658
## Complete CI = [242, 3074]
## Bootstrap pooled estimate = 1476
## Bootstrap weighted pooled estimate = 1461
## Bootstrap pooled CI = [66.5, 2885]
## 59% of bootstrap samples have confidence intervals that do not span zero.
## 59% positive.
## 0% negative.
## ctree Results:
## Complete estimate = 1598
## Complete CI = [-6.62, 3203]
## Bootstrap pooled estimate = 1465
## Bootstrap weighted pooled estimate = 1472
## Bootstrap pooled CI = [172, 2758]
## 38.1% of bootstrap samples have confidence intervals that do not span zero.
## 38.1% positive.
## 0% negative.
## rpart Results:
## Complete estimate = 1332
## Complete CI = [-295, 2959]
## Bootstrap pooled estimate = 1429
## Bootstrap weighted pooled estimate = 1442
## Bootstrap pooled CI = [-136, 2993]
## 32% of bootstrap samples have confidence intervals that do not span zero.
## 32% positive.
## 0% negative.
## Matching Results:
## Complete estimate = 861
## Complete CI = [234, 1487]
## Bootstrap pooled estimate = 1429
## Bootstrap weighted pooled estimate = 1396
## Bootstrap pooled CI = [-339, 3196]
## 86% of bootstrap samples have confidence intervals that do not span zero.
## 85% positive.
## 1% negative.
## Matching-1-to-3 Results:
## Complete estimate = 1536
## Complete CI = [1089, 1983]
## Bootstrap pooled estimate = 1450
## Bootstrap weighted pooled estimate = 1400
## Bootstrap pooled CI = [-135, 3034]
## 90% of bootstrap samples have confidence intervals that do not span zero.
## 90% positive.
## 0% negative.
## MatchIt Results:
## Complete estimate = 1772
## Complete CI = [370, 3174]
## Bootstrap pooled estimate = 1684
## Bootstrap weighted pooled estimate = 1637
## Bootstrap pooled CI = [260, 3108]
## 67% of bootstrap samples have confidence intervals that do not span zero.
## 67% positive.
## 0% negative.
plot(boot_out)
Figure 6.1: Mean difference across all bootstrap samples by method
boxplot(boot_out)
matrixplot(boot_out)
boot_balance <- balance(boot_out)
boot_balance## Unadjusted balance: 1.48309081605193## 0.04
## 0.08
## 0.05
## 0.06
## 0.01
## 0.06
## 0.04
## NA
## 0.07
## 0.07
## 0.05
## 0.08
plot(boot_balance)
boxplot(boot_balance) + geom_hline(yintercept=.1, color='red')
Details are available within the returned object
boot_balance$unadjusted## 3.51
## 5.46
## 1.12
## 1.16
## 0.66
## 0.89
## 0.39
## 0.44
## 0.72
## 0.49
boot_balance$complete## 0.04
## 0.00
## 0.00
## 0.01
## 0.00
## 0.16
## 0.03
## 0.16
## 0.05
## 0.04
## 0.02
## 0.06
## 0.09
## 0.15
## 0.14
## 0.04
## 0.01
## 0.02
## 0.04
## 0.05
## 0.08
## 0.04
## 0.00
## 0.09
## 0.02
## 0.08
## 0.10
## 0.09
## 0.01
## 0.02
## 0.03
## 0.08
## 0.02
## 0.09
## 0.02
## 0.07
## 0.00
## 0.09
## 0.05
## 0.06
## 0.00
## 0.00
## 0.03
## 0.09
## 0.01
## 0.07
## 0.01
## 0.04
## 0.06
## 0.06
## 0.06
## 0.02
## 0.05
## 0.08
## 0.03
## 0.03
## 0.01
## 0.10
## 0.00
## 0.05
boot_balance$pooled |> head()## 0.02
## 0.03
## 0.04
## 0.03
## 0.04
## 0.05
## 0.07
## 0.09
## 0.12
## NA
## 0.06
## 0.12
## 0.05
## 0.09
## 0.08
## 0.11
## 0.08
## 0.07
## 0.06
## 0.07
## 0.03
## 0.07
## 0.05
## 0.06
## 0.04
## 0.03
## 0.03
## 0.08
## 0.03
## 0.05
## 0.08
## 0.10
## 0.09
## 0.07
## 0.10
## 0.10