spatt {qte} | R Documentation |
spatt
Description
spatt
computes the Average Treatment Effect on the
Treated (ATT) using the method of Abadie (2005)
Usage
spatt(
formla,
xformla = NULL,
t,
tmin1,
tname,
data,
w = NULL,
panel = FALSE,
idname = NULL,
iters = 100,
alp = 0.05,
method = "logit",
plot = FALSE,
se = TRUE,
retEachIter = FALSE,
seedvec = NULL,
pl = FALSE,
cores = 2
)
Arguments
formla |
The formula y ~ d where y is the outcome and d is the treatment indicator (d should be binary) |
xformla |
A optional one sided formula for additional covariates that will be adjusted for. E.g ~ age + education. Additional covariates can also be passed by name using the x paramater. |
t |
The 3rd time period in the sample (this is the name of the column) |
tmin1 |
The 2nd time period in the sample (this is the name of the column) |
tname |
The name of the column containing the time periods |
data |
The name of the data.frame that contains the data |
w |
an additional vector of sampling weights |
panel |
Boolean indicating whether the data is panel or repeated cross sections |
idname |
The individual (cross-sectional unit) id name |
iters |
The number of iterations to compute bootstrap standard errors. This is only used if se=TRUE |
alp |
The significance level used for constructing bootstrap confidence intervals |
method |
The method for estimating the propensity score when covariates are included |
plot |
Boolean whether or not the estimated QTET should be plotted |
se |
Boolean whether or not to compute standard errors |
retEachIter |
Boolean whether or not to return list of results from each iteration of the bootstrap procedure |
seedvec |
Optional value to set random seed; can possibly be used in conjunction with bootstrapping standard errors. |
pl |
boolean for whether or not to compute bootstrap error in parallel. Note that computing standard errors in parallel is a new feature and may not work at all on Windows. |
cores |
the number of cores to use if bootstrap standard errors are computed in parallel |
Value
QTE
object
References
Abadie (2005)
Examples
##load the data
data(lalonde)
## Run the panel.qtet method on the experimental data with no covariates
att1 <- spatt(re ~ treat, t=1978, tmin1=1975, tname="year",
x=NULL, data=lalonde.psid.panel, idname="id", se=FALSE)
summary(att1)
## Run the panel.qtet method on the observational data with no covariates