Description Usage Arguments Details Value See Also
iptw
uses gbm
to estimate
propensity scores for sequential treatments.
1 2 3 4 5 6 7 8 9 10 |
formula |
Either a single formula (long format) or a list with formulas |
data |
The dataset, includes treatment assignment as well as covariates |
timeInvariant |
An optional formula (with no left-hand variable) specifying time-invariant chararacteristics. |
n.trees |
number of gbm iterations passed on to |
stop.method |
A method or methods of measuring and summarizing balance across
pretreatment variables. Current options are |
cumulative |
If |
timeIndicators |
For long format fits, a vector of times for each observation. |
ID |
For long format fits, a vector of numeric identifiers for unique analytic units. |
priorTreatment |
For long format fits, includes treatment levels from previous times if |
... |
Additional arguments that are passed to |
This function uses generalized boosted models to estimate inverse probability of treatment weights for sequential treatments.
Returns an object of class iptw
, a list containing
psList |
A list of ps objects with length equal to the number of time periods. |
estimand |
The specified estimand. |
stop.methods |
The stopping rules used to optimize iptw balance. |
nFits |
The number of ps objects (i.e., the number of distinct time points.) |
uniqueTimes |
The unique times in the specified model. |
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