otherCausal {causalGel} | R Documentation |
This documentation file presents a collection of popular methods used to estimate the average causal effect, the causal effect on the treated and the causal effect on the non-treated.
matching(form, balm, data, type=c("ACE","ACT","ACC"), M=4, adjust=FALSE, matchPS=FALSE, psForm=NULL, bcForm=NULL) LLmatching(form, psForm, data, type=c("ACE","ACT","ACC"), kern=c("Gaussian","Epanechnikov"),tol=1e-4, h=NULL, from=.00001, to=5, ngrid=10, maxit=100, hMethod=c("Brent","Grid")) ipw(form, psForm, data, type=c("ACE","ACT","ACC"), normalized=FALSE, ...)
form |
A formula that links the outcome variable to the treatment indicator. For the moment, only one treatment group is allowed. |
balm |
A formula or a matrix with balancing covariates to be matched. |
data |
A data.frame or a matrix with column names. |
type |
The type of causal effect to compute. |
M |
The minimum number of matches |
adjust |
Should we apply a bias correction to the estimate. |
matchPS |
Should we match the propensity scores instead of the covariates. |
psForm |
It is the |
bcForm |
A formula that represents the right hand side in the regression used for the bias correction. |
kern |
The type of kernel to use in the local linear regression method. |
tol |
The tolerance level for the stopping rule used to compute the optimal bandwidth. |
h |
A fixed bandwidth. By default, the optimal bandwidth is found by minimizing a cross-validation. |
from |
The lower bound for the search of the optimal bandwidth. |
to |
The upper bound for the search of the optimal bandwidth. |
ngrid |
The number of grid points if the optimal bandwidth is obtained by grid search. |
maxit |
The maximum number of iterations for the minimization of the cross-validation. |
hMethod |
The method used to find the optimal bandwidth. |
normalized |
Should the weights be normalized. If set to
|
... |
Additional arguments to pass to |
All methods return an object of classes "causalfit"
.
data(nsw) balm <- ~age+ed+black+hisp:married+nodeg+re75+I(re75^2) g <- re78~treat ps <- treat~age+ed+black+hisp:married+nodeg+re75+I(re75^2) fit1 <- matching(g, balm, nsw, "ACE", adjust=TRUE) fit1 fit2 <- LLmatching(g, ps, nsw, "ACE") fit2 fit3 <- ipw(g, ps, nsw, "ACE", normalized=TRUE) fit3