twoarmsurv.dr {precmed}

Doubly robust estimators of the coefficients in the contrast regression as well as their covariance matrix and convergence information

Description

Newton-Raphson algorithm is used to solve the estimating equation bar S_n (delta) = 0

Usage

twoarmsurv.dr(
  ynew,
  dnew,
  trt,
  x.cate,
  tau0,
  weightsurv,
  ps,
  f1.predictor,
  f0.predictor,
  error.maxNR = 0.001,
  max.iterNR = 100,
  tune = c(0.5, 2)
)

Arguments

ynew

Truncated survival time; vector of size n

dnew

Event indicator after truncation; vector of size n

trt

Treatment received; vector of size n with treatment coded as 0/1.

x.cate

Matrix of p.cate baseline covariates specified in the outcome model; dimension n by p.cate.

tau0

The truncation time for defining restricted mean time lost.

weightsurv

Estimated inverse probability of censoring weights with truncation for all observations; vector of size n.

ps

Estimated propensity scores for all observations; vector of size n

f1.predictor

Initial predictions of the outcome (restricted mean time loss) conditioned on the covariates x.cate for treatment group trt = 1; mu_1(x.cate), step 1 in the two regression; vector of size n

f0.predictor

Initial predictions of the outcome (restricted mean time loss) conditioned on the covariates x.cate for treatment group trt = 0; mu_0(x.cate), step 1 in the two regression; vector of size n

error.maxNR

A numerical value > 0 indicating the minimum value of the mean absolute error in Newton Raphson algorithm. Used only if score.method = 'contrastReg'. Default is 0.001.

max.iterNR

A positive integer indicating the maximum number of iterations in the Newton Raphson algorithm. Used only if score.method = 'contrastReg'. Default is 100.

tune

A vector of 2 numerical values > 0 specifying tuning parameters for the Newton Raphson algorithm. tune[1] is the step size, tune[2] specifies a quantity to be added to diagonal of the slope matrix to prevent singularity. Used only if score.method = 'contrastReg'. Default is c(0.5, 2).

Value

coef: Doubly robust estimators of the contrast regression coefficients delta_0; vector of size p.cate + 1 (intercept included) converge: Indicator that the Newton Raphson algorithm converged for delta_0; boolean