estimateEffect: Estimate Effect after matching

In cardiomoon/webrPSM: Propensity Score Matching for Web-R

Estimate Effect after matching

Description

Estimate Effect after matching

Usage

estimateEffect(
  out,
  mode = "continuous",
  multiple = TRUE,
  dep = "",
  time = "",
  status = "",
  covarCentering = FALSE,
  withinSubclass = FALSE,
  digits = 2,
  sedigits = 2,
  pdigits = 4,
  se = TRUE,
  print = TRUE
)

Arguments

out	An object of class "matchit"
mode	One of c("continuous","binary","survival")
multiple	logical Whether or not perform multiple regression
dep	Name of dependent variable
time	Name of time variable
status	Name of status variable
covarCentering	logical
withinSubclass	logical
digits	integer indicating the number of decimal places
sedigits	digits for standard error
pdigits	digits for p value
se	logical If true, report se. If false report confidence interval
print	logical

Examples

library(MatchIt)
library(survival)
out <- matchit(A ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9, data = exData)
estimateEffect(out,dep=c("Y_C"),multiple=FALSE)
estimateEffect(out,dep=c("Y_C"))
estimateEffect(out,dep=c("Y_C","Y_B"))
estimateEffect(out,mode="binary",dep=c("Y_B"),multiple=FALSE)
estimateEffect(out,mode="binary",dep=c("Y_B"))
estimateEffect(out,mode="survival",dep=c("Y_S"),multiple=FALSE)
estimateEffect(out,mode="survival",dep=c("Y_S"))
## Not run: 
out=matchit(A ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9, data = exData,
   link = 'linear.logit', caliper = .1, ratio = 3, replace = TRUE)
estimateEffect(out,dep=c("Y_C"),multiple=FALSE)
estimateEffect(out,dep=c("Y_C"))
estimateEffect(out,mode="binary",dep=c("Y_B"),multiple=FALSE)
estimateEffect(out,mode="binary",dep=c("Y_B"))
estimateEffect(out,mode="survival",dep=c("Y_S"),multiple=FALSE)
estimateEffect(out,mode="survival",dep=c("Y_S"))
out=matchit(A ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9, data = exData,
method = "full", estimand = "ATE")
estimateEffect(out,dep=c("Y_C"),multiple=FALSE)
estimateEffect(out,dep=c("Y_C"),covarCentering=TRUE)
estimateEffect(out,mode="binary",dep=c("Y_B"),multiple=FALSE)
estimateEffect(out,mode="survival",dep=c("Y_S"),multiple=FALSE)
out=matchit(A ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9, data = exData,
method = "subclass", estimand = "ATT",subclass = 8)
estimateEffect(out,dep=c("Y_C"),multiple=FALSE)
estimateEffect(out,dep=c("Y_C"),multiple=FALSE,withinSubclass=TRUE)
estimateEffect(out,mode="binary",dep=c("Y_B"),multiple=FALSE)
estimateEffect(out,mode="binary",dep=c("Y_B"))
estimateEffect(out,mode="survival",dep=c("Y_S"),multiple=FALSE)
out=matchit(A ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9, data = exData,
method = "full", estimand = "ATT")
estimateEffect(out,mode="binary",dep=c("Y_B"))
estimateEffect(out,mode="continuous",dep=c("Y_B"))  # for conditional effect
out=matchit(A ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9, data = swData,
method = "full", estimand = "ATE",s.weights="SW")
estimateEffect(out,dep=c("Y_C"))
x=matchit(treat ~ age + educ + race + married+nodegree + re74 + re75, data =lalonde,
   method="exact")
estimateEffect(x,dep=c("re78"))
data(GBSG2,package="TH.data")
out=matchit(horTh~age+menostat+tsize+tgrade+pnodes+progrec+estrec,data=GBSG2)
estimateEffect(out,mode="binary",dep="cens")
estimateEffect(out,mode="survival",dep="cens",time="time",status="cens")

## End(Not run)

cardiomoon/webrPSM documentation built on Feb. 2, 2024, 3:55 a.m.