checkresults

This function draws a quantile plot for Monte Carlo assessments of fit to the corrected proportional hazards fit.

Proportional hazards estimation in the presence of a partially monotone likelihood has difficulties, in that finite estimators do not exist.  These difficulties are related to those arising from logistic and multinomial regression.  References for methods are given in the separate function documents.  Supported by grant NSF DMS 1712839.

John E Kolassa

PHInfiniteEstimates

Tools for Inference in the Presence of a Monotone Likelihood

checkresults function

<dl><dt>regnsimulation</dt>
<dd>A structure with a component out, matrix with columns representing definitions of p-values and as many rows as there MC samples.</dd>
<dt>frac</dt>
<dd>Proportion for bottom of distribution to be assessed.</dd></dl>

Arguments

Produce a graphical assessment of Monte Carlo experiment on fidelity of proportional hazards regression to the uniform ideal. — checkresults

<dl>

<dt>regnsimulation</dt>
<dd>A structure with a component out, matrix with columns representing definitions of p-values and as many rows as there MC samples.</dd>


<dt>frac</dt>
<dd>Proportion for bottom of distribution to be assessed.</dd>

</dl>

checkresults: Produce a graphical assessment of Monte Carlo experiment on fidelity of proportional hazards regression to the uniform ideal.

Description

Usage

Value

Arguments