causalGEL {causalGel} | R Documentation |
It fit a causality model using balancing based on GEL methods. It
creates an object of class "causalGelfit"
.
causalGEL(g, balm, data, theta0=NULL, momType=c("ACE","ACT","ACC", "uncondBal","fixedMom"), popMom = NULL, rhoFct=NULL,ACTmom=1L, gelType = c("EL", "ET", "EEL", "ETEL", "HD", "ETHD","REEL"), initTheta = c("gmm","theta0"), getVcov=FALSE, lambda0=NULL, cstLHS=NULL, cstRHS=NULL, lamSlv=NULL, coefSlv= c("optim","nlminb","constrOptim"), lControl=list(), tControl=list(), restrictLam=FALSE, orthoBases=FALSE)
g |
A formula that links the outcome variable to the treatment indicators. |
balm |
A formula or a matrix with balancing covariates |
data |
A data.frame or a matrix with column names. |
theta0 |
A vector of starting values (optional). If not provided, the least squares method is use to generate them |
momType |
How the moments of the covariates should be balanced. By default, it is balanced using the sample mean of the covariates, which corresponds to the ACE. Alternatively, to the sample moments of the treated group (ACT), the control group (ACC), or to a known population mean. The option 'uncondBal' means that it is unconditionally balanced. |
popMom |
A vector of population moments to use for balancing. It can be used if those moments are available from a census, for example. When available, it greatly improves efficiency. |
rhoFct |
An optional function that return ρ(v). This is
for users who want a GEL model that is not built in the package. The
four arguments of the function must be |
ACTmom |
When |
gelType |
"EL" for empirical likelihood, "ET" for exponential tilting, "EEL" for Euclidean empirical likelihood, "ETEL" for exponentially tilted empirical likelihood of Schennach(2007), "HD" for Hellinger Distance of Kitamura-Otsu-Evdokimov (2013), and "ETHD" for the exponentially tilted Hellinger distance of Antoine-Dovonon (2015). "REEL" is a restricted version of "EEL" in which the probabilities are bounded below by zero. In that case, an analytical Kuhn-Tucker method is used to find the solution. |
initTheta |
Method to obtain the starting values for the coefficient vector. By default the GMM estimate with identity matrix is used. The second argument means that the theta0 of the object, if any, should be used. |
lambda0 |
Manual starting values for the Lagrange multiplier. By default, it is a vector of zeros. |
cstLHS |
The left hand side of the constraints to impose on the
coefficients. See |
cstRHS |
The right hand side of the constraints to impose on the
coefficients. See |
getVcov |
Should the method computes the covariance matrices of the coefficients and Lagrange multipliers. |
lamSlv |
An alternative solver for the Lagrange multiplier. By
default, either |
coefSlv |
Minimization solver for the coefficient vector. |
lControl |
A list of controls for the Lagrange multiplier algorithm. |
tControl |
A list of controls for the coefficient algorithm. |
restrictLam |
Should we restrict the lambdas for which the analytical solution is 0 to be fixed at 0? |
orthoBases |
If |
'causalGEL' returns an object of classesof "causalGelfit"
.
data(nsw) balm <- ~age+ed+black+hisp:married+nodeg+re75+I(re75^2) g <- re78~treat fit1 <- causalGEL(g, balm, nsw, gelType="ET") fit1 fit2 <- causalGEL(g, balm, nsw, gelType="EL") fit2