trips | R Documentation |
The propensity score is
e(X)=P({ W }=1|X)
This function will estimate the propensity scores for each pair of groups (e.g. two treatments and one control).
trips(
thedata,
treat,
formu = ~.,
groups = unique(treat),
nstrata = 5,
method = "logistic",
...
)
thedata |
the data frame. |
treat |
vector or factor indicating the treatment/control assignment for
|
formu |
the logistic regression formula. Note that the dependent variable should not be specified and will be modified. |
groups |
a vector of exactly length three corresponding the values in
|
nstrata |
the number of strata marks to plot on the edge. |
method |
the method to use to estimate the propensity scores. Current options are logistic or randomForest. |
... |
other parameters passed to [stats::glm()]. |
{ PS }_{ 1 }=e({ X }_{ { T }_{ 1 }C })=Pr(z=1|{ X }_{ { T }_{ 1 }C })
{ PS }_{ 2 }=e({ X }_{ { T }_{ 2 }C })=Pr(z=1|{ X }_{ { T }_{ 2 }C })
{ PS }_{ 3 }=e({ X }_{ { T }_{ 2 }{ T }_{ 1 } })=Pr(z=1|{ X }_{ { T }_{ 2 }{ T }_{ 1 } })
## Not run:
data(tutoring)
formu <- ~ Gender + Ethnicity + Military + ESL + EdMother + EdFather + Age +
Employment + Income + Transfer + GPA
tpsa <- trips(tutoring, tutoring$treat, formu)
head(tpsa)
## End(Not run)
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