heinzeschemper: Simulate operating characteristics of repaired Cox regression...

In PHInfiniteEstimates: Tools for Inference in the Presence of a Monotone Likelihood

Simulate operating characteristics of repaired Cox regression and competitors.

Description

This function is intended to verify the operating characteristics of the approximate conditional inferential approach of \insertCitekz19;textualPHInfiniteEstimates to proportional hazards regression. An exponential regression model, corresponding to the proportional hazards regression model, is fit to the data, and new data sets are simulated from this model. P-values are calculated for these new data sets, and their empirical distribution is compared to the theoretical uniform distribution.

Usage

heinzeschemper(
  nobs = 50,
  k = 5,
  B = 1,
  c = 0,
  nsamp = 1000,
  beta = NULL,
  add = NULL,
  half = NULL,
  verbose = FALSE,
  smoothfirst = FALSE
)

Arguments

nobs	number of observations in simulated data set.
k	number of covariates in simulated data set. Each covariate is dochotomous.
B	odds of 1 vs. 0 in dichotomous variables.
c	censoring proportion.
nsamp	number of samples.
beta	regression parameters, all zeros if null, and all the same value if a scalar.
add	partial simulation results to be added to, or NULL if de novo.
half	does nothing; provided for compatabilitity with simcode.
verbose	Triggers verbose messages.
smoothfirst	Triggers normal rather than dichotomous interest covariate.

Value

a list with components

• out matrix with columns corresponding to p-values.

PHInfiniteEstimates documentation built on Nov. 24, 2023, 9:06 a.m.