testing the significance of the covariates from a coxtv or coxtp object using a Wald test statistic

Source: R/tvef.ph.R

Testing the significance of the covariates at each time point.

tvef.zero.time(fit, time, parm)

Arguments

fit

fitted coxtv or coxtp model.

time

the time points to test if the covariate is significant or not.

parm

the names of parameters to be tested.

Value

tvef.zero.time produces a list of length nvars. Each element of the list is a matrix with respect to a covariate. The matrix is of dimension len_unique_t by 4, where len_unique_t is the length of unique observed event time. Each row corresponds to the testing result at that time. The four columns give the estimations, standard error, test-statistic and P-value.

See also

tvef.ph tvef.zero

Examples

data(ExampleData)
z <- ExampleData$z
time  <- ExampleData$time
event <- ExampleData$event
fit   <- coxtv(event = event, z = z, time = time)
#> Iter 1: Obj fun = -3.2982771; Stopping crit = 1.0000000e+00;
#> Iter 2: Obj fun = -3.2916285; Stopping crit = 2.1424865e-02;
#> Iter 3: Obj fun = -3.2916034; Stopping crit = 8.0884492e-05;
#> Iter 4: Obj fun = -3.2916034; Stopping crit = 1.8232153e-09;
#> Algorithm converged after 4 iterations!
test  <- tvef.zero.time(fit)