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landpred (version 1.2)

Landmark Prediction of a Survival Outcome

Description

Provides functions for landmark prediction of a survival outcome incorporating covariate and short-term event information. For more information about landmark prediction please see: Parast, Layla, Su-Chun Cheng, and Tianxi Cai. Incorporating short-term outcome information to predict long-term survival with discrete markers. Biometrical Journal 53.2 (2011): 294-307, .

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Version

Install

install.packages('landpred')

Monthly Downloads

237

Version

1.2

License

GPL

Maintainer

Layla Parast

Last Published

August 26th, 2023

Functions in landpred (1.2)

landpred-package

Landmark Prediction of a Survival Outcome
prob2.single

Estimates P(TL <t0+tau | TL > t0, Z, TS==ts) for a single t.
cumsum2

Helper function
mse.BW

Helper function for optimize.mse.BW.
VTM

Helper function, repeats a row.
helper.si

Helper function for AUC.landmark
Prob.Covariate.ShortEvent

Estimates P(TL <t0+tau | TL > t0, Z, min(TS, t0), I(TS<=t0)), i.e. given discrete covariate and TS information.
optimize.mse.BW

Calculates initial optimal bandwidth.
Prob.Null

Estimates P(TL <t0+tau | TL > t0).
Prob.Covariate

Estimates P(TL <t0+tau | TL > t0, Z), i.e. given discrete covariate.
Ghat.FUN

Calculates the Kaplan Meier survival probability for censoring
BS.landmark

Estimates the Brier score.
data_example_landpred

Hypothetical data to be used in examples.
Prob2.k.t

Estimates P(TL <t0+tau | TL > t0, Z, TS==ts).
Prob2

Estimates P(TL <t0+tau | TL > t0, Z, TS>t0).
Wi.FUN

Computes the inverse probability of censoring weights for a specific t0 and tau
AUC.landmark

Estimates the area under the ROC curve (AUC).
Kern.FUN

Calculates kernel matrix