estSLSE {causalSLSE} | R Documentation |
Least Squares Estimate of cslseModel
or slseModel
Objects
Description
This is the main function to estimate cslseModel
or
slseModel
objects. It generates the basis functions based on the
knots specified in the model and estimates it by least squares.
Usage
## S3 method for class 'cslseModel'
estSLSE(model, selKnots, ...)
## S3 method for class 'slseModel'
estSLSE(model, selKnots, ...)
Arguments
model |
A model of class |
selKnots |
An optional list of integers to select the knots from
the list of knots specified by the model. If the model is a
|
... |
Additional arguments to pass to other methods. Currently not used. |
Details
The method for slseModel
objects generates the matrix
of basis functions implied by the set of knots included in the model and
estimate the model by the least squares. Let Y
be the
outcome and U
be the matrix of basis functions. Then, the
function estimates the model using the code lm(Y~U)
.
For cslseModel
, we could estimate the model using
lm(Y~Z+I(Z-1)+I(U0*(1-Z))+I(U1*Z))
, where Z
is a binary
variable equal to 1 for the treated and 0 for the nontreated, and
U0
and U1
are the matrices of basis functions for the
nontreated and treated, but the model is estimated separately for each
group. Therefore, the function estSLSE.cslseModel
calls the
function estSLSE.slseModel
for each slseModel
objects
included in the cslseModel
object.
Value
It returns an object of class slseFit
or cslseFit
depending on which method is called. An object of class slseFit
is a list with the following elements:
LSE |
This is the least squares estimate of the semiparametric
model. It is an object of class |
model |
An object of class |
An object of class cslseFit
is a list of slseFit
objects,
one for each treatment group. It also contains the following additional
attributes:
treatedVar |
The name of the variable in the dataset that represents the treatment indicator. |
groupInd |
A named vector with the value of the treatment indicator corresponding do each treatment group. |
Examples
data(simDat3)
## Estimating a causal semiparametric model
mod1 <- cslseModel(Y ~ Z | ~ X1 * X2, data = simDat3)
fit1 <- estSLSE(mod1)
## Estimating a semiparametric model
mod2 <- slseModel(Y ~ X1 * X2, data = simDat3)
fit2 <- estSLSE(mod2)