Description Usage Arguments Details Value Author(s) References See Also
ps
calculates propensity scores and diagnoses them using
a variety of methods, but centered on using boosted logistic regression as
implemented in gbm
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 |
formula |
A formula for the propensity score model with the treatment indicator on the left side of the formula and the potential confounding variables on the right side. |
data |
The dataset, includes treatment assignment as well as covariates |
n.trees |
number of gbm iterations passed on to |
interaction.depth |
|
shrinkage |
|
bag.fraction |
|
perm.test.iters |
a non-negative integer giving the number of iterations
of the permutation test for the KS statistic. If |
print.level |
the amount of detail to print to the screen |
iterlim |
maximum number of iterations for the direct optimization |
verbose |
if TRUE, lots of information will be printed to monitor the the progress of the fitting |
estimand |
The causal effect of interest. Options are |
stop.method |
A method or methods of measuring and summarizing balance across
pretreatment variables. Current options are |
sampw |
Optional sampling weights. |
multinom |
Set to true only when called from |
... |
Additional arguments. |
formula
should be something like "treatment ~ X1 + X2 + X3". The
treatment variable should be a 0/1 indicator. There is no need to specify
interaction terms in the formula. interaction.depth
controls the level
of interactions to allow in the propensity score model.
Note that — unlike earlier versions of twang
— plotting functions
are no longer included in the ps()
function. See
plot
for details of the plots.
Returns an object of class ps
, a list containing
gbm.obj |
The returned |
treat |
The treatment variable. |
desc |
a list containing balance tables for each method selected in
|
datestamp |
Records the date of the analysis |
parameters |
Saves the |
alerts |
Text containing any warnings accumulated during the estimation |
iters |
A sequence of iterations used in the GBM fits used by |
balance |
The balance measures for the pretreatment covariates, with a column for each
|
n.trees |
Maximum number of trees considered in GBM fit. |
data |
Data as specified in the |
Greg Ridgeway gregr@rand.org, Dan McCaffrey danielm@rand.org, Andrew Morral morral@rand.org, Lane Burgette burgette@rand.org
Dan McCaffrey, G. Ridgeway, Andrew Morral (2004). “Propensity Score Estimation with Boosted Regression for Evaluating Adolescent Substance Abuse Treatment,” Psychological Methods 9(4):403-425.
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