control_step: Control function for subgroup treatment effect pattern (STEP)...

View source: R/control_step.R

control_stepR Documentation

Control function for subgroup treatment effect pattern (STEP) calculations

Description

[Stable]

This is an auxiliary function for controlling arguments for STEP calculations.

Usage

control_step(
  biomarker = NULL,
  use_percentile = TRUE,
  bandwidth,
  degree = 0L,
  num_points = 39L
)

Arguments

biomarker

(numeric or NULL)
optional provision of the numeric biomarker variable, which could be used to infer bandwidth, see below.

use_percentile

(flag)
if TRUE, the running windows are created according to quantiles rather than actual values, i.e. the bandwidth refers to the percentage of data covered in each window. Suggest TRUE if the biomarker variable is not uniformly distributed.

bandwidth

(numeric(1) or NULL)
indicating the bandwidth of each window. Depending on the argument use_percentile, it can be either the length of actual-value windows on the real biomarker scale, or percentage windows. If use_percentile = TRUE, it should be a number between 0 and 1. If NULL, treat the bandwidth to be infinity, which means only one global model will be fitted. By default, 0.25 is used for percentage windows and one quarter of the range of the biomarker variable for actual-value windows.

degree

(integer(1))
the degree of polynomial function of the biomarker as an interaction term with the treatment arm fitted at each window. If 0 (default), then the biomarker variable is not included in the model fitted in each biomarker window.

num_points

(integer(1))
the number of points at which the hazard ratios are estimated. The smallest number is 2.

Value

A list of components with the same names as the arguments, except biomarker which is just used to calculate the bandwidth in case that actual biomarker windows are requested.

Examples

# Provide biomarker values and request actual values to be used,
# so that bandwidth is chosen from range.
control_step(biomarker = 1:10, use_percentile = FALSE)

# Use a global model with quadratic biomarker interaction term.
control_step(bandwidth = NULL, degree = 2)

# Reduce number of points to be used.
control_step(num_points = 10)


tern documentation built on Sept. 24, 2024, 9:06 a.m.