gen_resp

Generate random outcome (response) according to a ground-truth logistic model

Simulation

Predictive scores must be updated with care, because actions taken on the basis of existing risk scores causes bias in risk estimates from the updated score. A holdout set is a straightforward way to manage this problem: a proportion of the population is 'held-out' from computation of the previous risk score. This package provides tools to estimate a size for this holdout set and associated errors. Comprehensive vignettes are included. Please see: Haidar-Wehbe S, Emerson SR, Aslett LJM, Liley J (2022) <doi:10.48550/arXiv.2202.06374> (to appear in Annals of Applied Statistics) for details of methods.

James Liley

OptHoldoutSize

Estimation of Optimal Size for a Holdout Set for Updating a
Predictive Score

Sami Haidar-Wehbe

Sam Emerson

Louis Aslett

gen_resp function

<dl><dt>X</dt>
<dd>Matrix of observations</dd>
<dt>coefs</dt>
<dd>Vector of coefficients for logistic model. If NA, random coefficients are generated. Defaults to NA</dd>
<dt>coefs_sd</dt>
<dd>If random coefficients are generated, use this SD (mean 0)</dd>
<dt>retprobs</dt>
<dd>If TRUE, return class probability; otherwise, return classes. Defaults to FALSE</dd></dl>

Arguments

Generate response — gen_resp

<dl>

<dt>X</dt>
<dd>Matrix of observations</dd>


<dt>coefs</dt>
<dd>Vector of coefficients for logistic model. If NA, random coefficients are generated. Defaults to NA</dd>


<dt>coefs_sd</dt>
<dd>If random coefficients are generated, use this SD (mean 0)</dd>


<dt>retprobs</dt>
<dd>If TRUE, return class probability; otherwise, return classes. Defaults to FALSE</dd>

</dl>

gen_resp: Generate response

Description

Usage

Value

Arguments

Examples