cste_surv {CSTE}

Estimate the CSTE curve for time to event outcome with right censoring.

Description

Estimate the CSTE curve for time to event outcome with right censoring. The working model is

\lambda(t| X, Z) = \lambda_0(t) \exp(\beta^T(X)Z + g(X)),

which implies that CSTE(x) = \beta(x).

Usage

cste_surv(x, y, z, s, h)

Arguments

x

samples of biomarker (or covariate) which is a n*1 vector and should be scaled between 0 and 1.

y

samples of time to event which is a n*1 vector.

z

samples of treatment indicator which is a n*K matrix.

s

samples of censoring indicator which is a n*1 vector.

h

kernel bandwidth.

Value

A n*K matrix, estimation of \beta(x).

References

Ma Y. and Zhou X. (2017). Treatment selection in a randomized clinical trial via covariate-specific treatment effect curves, Statistical Methods in Medical Research, 26(1), 124-141.

See Also

cste_surv_SCB