Description Usage Arguments References Examples
View source: R/modelDependence.R
modelDependence()
is used to compute the Athey-Imbens
measure of sensitivity to model specification or to estimate
the range of possible treatment effect estimates by extreme
bounds. If a base.form is given, the Athey-Imbens estimates
are calculated. To use extreme bounds, give either
model.dependence.ests or specifictions.
1 2 3 4 5 6 7 8 9 10 11 12 |
dataset |
A data frame containing the variables in the model. |
treatment |
The treatment (quantity of interest). The measure of model dependence is with respect to estimates of this quantity. Must be in base.form. |
outcome |
The outcome variable. |
covariates |
A vector of the names of covariates necessary to perform the extreme bounds (treatment, outcome, and control variables). |
model.dependence.ests |
For extreme bounds, the number of specifications to estimate. |
base.form |
The base formula that is to be evaluated. |
verbose |
If TRUE, additional information is printed. |
seed |
Seed for the random number generator. |
cutpoints |
A list where the keys are variables names and the values are cutpoints. If specified, cutpoints for these variables will not be estimated. Otherwise, cutpoints are estimated with segmented regression. |
median |
If TRUE, the cutpoint is set at the median. If false, the cutpoint is estimated with segmeted (piecewise) regression. |
ratio |
Either "fixed" or "variable". If fixed, covariates are not reweighted according to their matches during the extreme bounds procedure. If variable, they are reweighted. |
specifications |
A vector of model formulas to be used in the extreme bounds procedure. If not supplied, they are drawn from all possible specifications using up to third degree polynomials and double interactions. |
Athey, Susan, and Guido W. Imbens. "A Measure of Robustness to Misspecification." (2014).
1 2 3 4 5 6 7 8 9 10 11 | data(lalonde)
treatment <- 'treat'
base.form <- as.formula('re78 ~ treat + age + education
+ black + hispanic + married +
nodegree + re74 + re75')
md <- modelDependence(dataset = lalonde, treatment = treatment,
base.form = base.form,
cutpoints = list('age' = mean(lalonde$age)))
print(md)
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