tool: tool functions

In CSTE: Covariate Specific Treatment Effect (CSTE) Curve

Description

tool functions

tool functions

Usage

ztrans(z, x, x0, h)

lpl(input, x, x0, R, z, s, h)

g(x0, sep, sloped)

cntcov(l, beta0, beta0dot, g0dot, x, x0, R, Z, s, h, sep, sloped)

sampleQ(i, l, stdel, stgam, std, x, R, Z, s, h, sep, sloped, m)

getthres(alpha, l, stdel, stgam, std, x, R, Z, s, h, sep, sloped, m)

get.bound(thres, l, stdel, stgam, std, x, R, Z, s, h, sep, sloped)

pu(x, beta)

pu_inv(x, beta, u)

normalize(x)

logitinv(x)

my_logit(x, y, off = NULL, beta = NULL, lam = 0, pen = 2)

my_surv(x, y, atrisk, off = NULL, beta = NULL, lam = 0)

prev_fit_cste(u1, u2, fit)

Arguments

z	treatment indicators which is n*K matrix.
x	numeric vector or matrix.
x0	biomarkers at a fixed point.
h	kernel bandwidth.
input	parameters with dimension (2*K+1).
R	indicator matrix of individuals at risk prior to y_i.
s	censoring indicator which is a n*1 vector.
sloped	the first derivative of g.
l	contraction vector with dimension K.
beta0, beta0dot	the value of beta and its first derivative at x0.
g0dot	the first derivative of g0 at x0.
i	the i-th observation.
stdel, stgam, std	store the values of beta0, beta0dot, and godot at each x_i.
m	number of turns of resampling.
alpha	the (1-alpha)-confidence level of SCB.
thres	the output of getthres function.
y, u, u1, u2, beta, atrisk	numeric vector.
off	numeric value, offset.
lam	numeric value, penalty parameter.
pen	hyper-parameter that used in MCP and SCAD penalty functions.
fit	a S3 class of cste.
seq	parameter for trapezoid rule.

Value

Intermediate results.

Intermediate results.

CSTE documentation built on Dec. 16, 2021, 9:07 a.m.