Set parameters controlling Cox model estimation of controlled effect curves

This should be used in conjunction with est_ce to set parameters controlling Cox model estimation of controlled effect curves; see examples.

Usage

params_ce_cox(spline_df = NA, spline_knots = NA, edge_ind = FALSE)

Arguments

spline_df

An integer; if the marker is modeled flexibly within the Cox model linear predictor as a natural cubic spline, this option controls the degrees of freedom in the spline; knots are chosen to be equally spaced across the range of the marker.

spline_knots

A numeric vector; as an alternative to specifying spline_df, the exact locations of the knots in the spline (including boundary knots) can be specified with this option.

edge_ind

Boolean. If TRUE, an indicator variable corresponding to the lower limit of the marker will be included in the Cox model linear predictor.

Value

A list of options.

Examples

data(hvtn505)
dat <- load_data(time="HIVwk28preunblfu", event="HIVwk28preunbl", vacc="trt",
                 marker="IgG_V2", covariates=c("age","BMI","bhvrisk"),
                 weights="wt", ph2="casecontrol", data=hvtn505)
# \donttest{
ests_cox <- est_ce(
  dat = dat,
  type = "Cox",
  t_0 = 578,
  params_cox = params_ce_cox(spline_df=4)
)
# }