weighted.tmle.predicted.values: IPCWTMLE2Phase IPCW-TMLE to output the TMLEs of predicted...
In brendalewisprice/IPCWTMLE2Phase: Inverse Probability of Censoring Weighted Targeted Minimum Loss-based Estimation for Two-Phase STudies
Description
Usage
Arguments
Value
Examples
View source: R/FunctionsForPackage09242019.R
Description
IPCW-TMLE outputting TMLEs of predicted values. This function only performs the TMLE step for targeting the predicted values. And does not output any additional estimates.
Usage
1
2
weighted.tmle.predicted.values(w, a, y, delta, Q.SL.library, g.SL.library,
wgts, max.wgt = Inf)
Arguments
w
The covariates
a
The treatment or exposure binary variable.
y
The outcome
Q.SL.library
SuperLearner library of algorithms for Q estimation
g.SL.library
SuperLearner library of algorithms for g estimation
wgts
observation level weights; should be 0 for delta=0
Value
fitted.values The predicted values for each observation from the TMLE
Examples
1
brendalewisprice/IPCWTMLE2Phase documentation built on Nov. 4, 2019, 8:12 a.m.
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Description Usage Arguments Value Examples
View source: R/FunctionsForPackage09242019.R
Description
IPCW-TMLE outputting TMLEs of predicted values. This function only performs the TMLE step for targeting the predicted values. And does not output any additional estimates.
Usage
1 2 | weighted.tmle.predicted.values(w, a, y, delta, Q.SL.library, g.SL.library,
wgts, max.wgt = Inf)
|
Arguments
w |
The covariates |
a |
The treatment or exposure binary variable. |
y |
The outcome |
Q.SL.library |
SuperLearner library of algorithms for Q estimation |
g.SL.library |
SuperLearner library of algorithms for g estimation |
wgts |
observation level weights; should be 0 for delta=0 |
Value
fitted.values The predicted values for each observation from the TMLE
Examples
1 |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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