pred.smooth.surv.new

observed event times in the control group in Study A

Axzero.f

event/censoring indicators in the control group in Study A

Adeltazero.f

surrogate marker values in the control group in Study A, NA for individuals not observable at the time the surrogate marker was measured

Aszero.f

surrogate marker values in one group (either treatment or control) in Study B

Bsnew.f

surrogate marker values in one group (either treatment or control) in Study B, optional

Bsnew2.f

time of interest

bandwidth, optional

weight used for perturbation resampling

weight.pred

TRUE or FALSE; indicates whether local constant extrapolation should be used

extrapolate

Helper function; calculates the estimated conditional probability of survival to time t given survival to the landmark time and given surrogate marker information.

robust

internal

smooth

nonparametric

survival

Provides functions to test for a treatment effect in terms of the difference in survival between a treatment group and a control group using surrogate marker information obtained at some early time point in a time-to-event outcome setting. Nonparametric kernel estimation is used to estimate the test statistic and perturbation resampling is used for variance estimation. More details will be available in the future in: Parast L, Cai T, Tian L (2019) ``Using a Surrogate Marker for Early Testing of a Treatment Effect" Biometrics, 75(4):1253-1263. <doi:10.1111/biom.13067>.

pred.smooth.surv.new: Calculates the conditional probability of survival to time t

Description

Usage

Arguments

Value

Details