india: India's National Health Insurance Program (RSBY)

In causalweight: Estimation Methods for Causal Inference Based on Inverse Probability Weighting

India's National Health Insurance Program (RSBY)

Description

A dataset which is a subset of the data from the randomized evaluation of the India's National Health Insurance Program (RSBY).

Usage

india

Format

A data frame with 11'089 rows and 7 variables:

X

individual identification

village_id

village identification

DistrictId

district identification

treat

treatment status (insurance)

mech

treatment assignment mechanism

enrolled

enrolled

EXPhosp_1

hospital expenditure

References

Imai, Kosuke; Jiang, Zhichao; Malani, Anup, 2020, "Replication Data for: Causal Inference with Interference and Noncompliance in Two-Stage Randomized Experiments.", https://doi.org/10.7910/DVN/N7D9LS, Harvard Dataverse, V1

Examples

## Not run: 
require(devtools)                        # load devtools package
install_github("szonszein/interference") # install interference package
library(interference)                    # load interference package
data(india)                              # load data
attach(india)                            # attach data
india=na.omit(india)                     # drop observations with missings
group=india$village_id                   # cluster id
group_tr=india$mech                      # indicator high treatment proportion
indiv_tr=india$treat                     # individual treatment (insurance)
obs_outcome=india$EXPhosp_1              # outcome  (hospital expenditure)
dat=data.frame(group,group_tr,indiv_tr,obs_outcome) # generate data frame
estimates_hierarchical(dat)
## End(Not run)             # run estimation

causalweight documentation built on Sept. 11, 2024, 8:06 p.m.