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tmle.npvi (version 0.9.3)

Targeted Learning of a NP Importance of a Continuous Exposure

Description

Targeted minimum loss estimation (TMLE) of a non-parametric variable importance measure of a continuous exposure 'X' on an outcome 'Y', taking baseline covariates 'W' into account.

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Version

Install

install.packages('tmle.npvi')

Monthly Downloads

3

Version

0.9.3

License

GPL

Maintainer

Pierre Neuvial

Last Published

February 5th, 2015

Functions in tmle.npvi (0.9.3)

SL.glm.theta

SL Wrapper for Estimation of Cond. Prob. of X=0 Given W
SL.glm.condExpXYgivenW

SL Wrapper for Estimation of Cond. Expect. of XY Given W
learnCondExpX2givenW

Estimation of Cond. Expect. of X^2 Given W
SL.glm.condExpX2givenW

SL Wrapper for Estimation of Cond. Expect. of X^2 Given W
superLearningLib

superLearningLib
learnDevTheta

Estimation of Cond. Expect. of (Y-thetaXW)^2 Given (X,W)
setConfLevel.NPVI

Sets Confidence Level
getHistory.NPVI

Returns History of TMLE Procedure
predict.SL.glm.theta

SL Wrapper for Estimation of Cond. Expect. of Y Given (X,W)
getPsi.NPVI

Returns Current Estimator
predict.SL.glm.g

SL Wrapper for Estimation of Cond. Prob. of X=0 Given W
getPValue.NPVI

Calculates a p-value from a NPVI object
learningLib

learningLib
as.character.NPVI

Returns a Description
tcga2012brca

Sample breast cancer data from TCGA
predict.SL.glm.condExpXYgivenW

SL Wrapper for Estimation of Cond. Expect. of XY Given W
learnMuAux

Estimation of Cond. Expect. of X Given (X!=x_0, W)
getPValue.matrix

Calculates a p-value from a matrix object of type 'history'
learnCondExpXYgivenW

Estimation of Cond. Expect. of XY Given W
getSample

Generates Simulated Data
getLightFit

Makes Lighter Fitted Object
learnTheta

Estimation of Cond. Expect. of Y given (X,W)
tmle.npvi

Targeted Minimum Loss Estimation of NPVI
getPsiSd.NPVI

Returns Current Estimated Standard Deviation of the Estimator
SL.glm.g

SL Wrapper for Estimation of Cond. Prob. of X=0 Given W
getObs.NPVI

Retrieves the Observations
extractXW

Removes the Y Column from Matrix of Observations
extractW

Extracts W Columns from Matrix of Observations
learnG

Estimation of Cond. Prob. of X=x_0 Given W
learnDevG

Estimation of Cond. Expect. of ((X==0)-gW)*effIC1 Given W
learnDevMu

Estimation of Cond. Expect. of (X-muW)*effIC1 Given W
predict.SL.glm.condExpX2givenW

SL Wrapper for Estimation of Cond. Expect. of X^2 Given W