Newton-Raphson algorithm is used to solve the estimating equation bar S_n (delta) = 0
twoarmglmcount.dr(
y,
x.cate,
time,
trt,
ps,
f1.predictor,
f0.predictor,
error.maxNR = 0.001,
max.iterNR = 150,
tune = c(0.5, 2)
)coef: Doubly robust estimators of the regression coefficients delta_0; vector of size p + 1 (intercept included)
vcov: Variance-covariance matrix of the estimated coefficient delta_0; matrix of size p + 1 by p + 1
converge: Indicator that the Newton Raphson algorithm converged for delta_0; boolean
Observed outcome; vector of size n
Matrix of p.cate baseline covariates; dimension n by p.cate
Log-transformed person-years of follow-up; vector of size n
Treatment received; vector of size n units with treatment coded as 0/1
Estimated propensity scores for all observations; vector of size n
Initial predictions of the outcome (expected number of relapses for one unit of exposure time)
conditioned on the covariates x for treatment group trt = 1; mu_1(x), step 1 in the two regression; vector of size n
Initial predictions of the outcome (expected number of relapses for one unit of exposure time)
conditioned on the covariates x for treatment group trt = 0; mu_0(x), step 1 in the two regression; vector of size n
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.
A positive integer indicating the maximum number of iterations in the
Newton Raphson algorithm. Used only if score.method = 'contrastReg'.
Default is 150.
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).