NCETS(Negative Control Exposure based on time-series studies),is an R package for causal effect estimation of environmental exposure on health outcome. Just taking advantage of a post-outcome exposure as an auxiliary variable, the NCETS can obtain an unbiased and robust causal effect estimation of exposure on outcome.
It is easy to install the development version of NCETS package using the 'devtools' package. The typical install time on a "normal" desktop computer is less than one minute.
# install.packages("devtools")
library(devtools)
install_github("yuyy-shandong/NCETS")
There are three main functions in NCETS package. One is diff_test for testing causal effect among time-varying Exposure. The second is ncets_cat which could eliminate the unmeasured confounders and estimate causal effect for categorical outcome. And the last one is ncets_con which eliminate the unmeasured confounders and estimate causal effect for continuous outcome. You can find the instructions by '?diff_test', '?ncets_cat' and '?ncets_con'.
library(NCETS)
?diff_test
?ncets_cat
?ncets_con
u <- rnorm(1000,0,1)
x1 <- 0.5*u +rnorm(1000,0,1)
x3 <- 0.5*u +rnorm(1000,0,1)
y <- 2*x1 + 1*u +rnorm(1000,0,1)
data <- data.frame (u,x1,x3,y)
model <- ncets_con (y~x1+x3, data = data, sdmethod ="normal",x1_name = "x1",x3_name = "x3",boots_no = NULL)
model
This R package is developed by Yuanyuan Yu, HongKai Li and Fuzhong Xue.