prostate_nodal

Prostatic acid phosphatase (PAP) emerged as the first clinically
useful tumor marker in the 1940s and 1950s. This data set contains the
serum levels of acid phosphatase of 53 patients that were confirmed to
have prostate cancer and whether the neighboring lymph nodes were involved.

datasets

Estimate cutpoints that optimize a specified metric in binary classification tasks
and validate performance using bootstrapping. Some methods for more robust cutpoint
estimation are supported, e.g. a parametric method assuming normal distributions,
bootstrapped cutpoints, and smoothing of the metric values per cutpoint using
Generalized Additive Models. Various plotting functions are included. For an overview
of the package see Thiele and Hirschfeld (2021) <doi:10.18637/jss.v098.i11>.

Christian Thiele

cutpointr

Determine and Evaluate Optimal Cutpoints in Binary
Classification Tasks

prostate_nodal function

A data frame with 53 rows and 2 variables:<dl class="dl-horizontal">
 <dt>acid_phosphatase</dt><dd>(numeric) Blood serum level of acid phosphatase</dd>
 <dt>nodal_involvement</dt><dd>(logical) Whether neighboring lymph nodes were involved</dd>
</dl>

Format

Nodal involvement and acid phosphatase levels in 53 prostate cancer patients — prostate_nodal

A data frame with 53 rows and 2 variables:<dl class='dl-horizontal'>
 <dt>acid_phosphatase</dt><dd>(numeric) Blood serum level of acid phosphatase</dd>
 <dt>nodal_involvement</dt><dd>(logical) Whether neighboring lymph nodes were involved</dd>
</dl>

prostate_nodal: Nodal involvement and acid phosphatase levels in 53 prostate cancer patients

Description

Usage

Arguments

Format