IWKME: The (S)IWKME estimator.

In otrKM: Optimal Treatment Regimes in Survival Contexts with Kaplan-Meier-Like Estimators

The (S)IWKME estimator.

Description

Given a predetermined t0 and eta, calculate t0-year potential survival probability based on the (S)IWKME estimator.

Usage

IWKME(eta, datalist, ps, t0, smooth = TRUE)

Arguments

eta	The parameters of the regime.
datalist	A list used to calculate the (S)IWKME estimator including treatment named a, observed time named obs.t, censoring indicator (0, censored) named delta, and baseline covariates used to assign treatment named l. Fps.IWKME can produce ps by positing logistic model. Notice that all the data in the datalist should be ordered by observed time.
ps	A list including the probability of receiving treatment given baseline covariates named fal.
t0	A predetermined time.
smooth	A logic variable indicating wether a smoothed estimator should be used.

Details

More details can be found in references.

Value

Estimated potential survival probability given eta and t0.

References

Jiang, R., Lu, W., Song, R., and Davidian, M. (2017) On estimation of optimal treatment regimes for maximizing t‐year survival probability. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 79: 1165-1185. DOI:10.1111/rssb.12201

Examples

# load data
data(simulation)
simulation=simulation[order(simulation$Survival),]

# convert the data into a datalist
datalist=list(z=simulation$Instrument,a=simulation$Treatment,
              obs.t=simulation$Survival,delta=simulation$Status,
              l=cbind(simulation$Covariate1,simulation$Covariate2))

# calculate ps
ps=Fps.IWKME(datalist)

# predetermined t0 and eta
t0=5
eta=c(1,2,3)

IWKME(eta, datalist, ps, t0, smooth=TRUE)

otrKM documentation built on July 9, 2023, 5:35 p.m.