endosim

The <code>endosim</code> data set was simulated based on the data analyzed in Rodriguez-Alvarez et al. (2011a,b) and presented in Botana et al. (2007) and Tome et al. (2008). The aim of these studies was to use the Body Mass Index (BMI) to detect patients having a higher risk of cardiovascular
problems, ascertaining the possible effect of age and gender on the accuracy of this measure.

datasets

Implements several nonparametric regression approaches for the inclusion of covariate information on the receiver operating characteristic (ROC) framework.

Maria Xose Rodriguez-Alvarez mxrodriguez@uvigo.es

npROCRegression

Kernel-Based Nonparametric ROC Regression Modelling

Maria Xose Rodriguez-Alvarez 

Javier Roca-Pardinas 

endosim function

A data frame with 2840 observations on the following 4 variables.<dl>
 	<dt><code>gender</code></dt>
<dd>patient's gender. Factor with <code>Male</code> and <code>Female</code> levels.</dd> 	<dt><code>age</code></dt>
<dd>patient's age.</dd> <dt><code>idf_status</code></dt>
<dd>true disease status (presence/absence of two of more cardiovascular risk factors according to the International Diabetes Federation). Numerical vector (0=absence, 1=presence).</dd> <dt><code>bmi</code></dt>
<dd>patient's body mass index.</dd> 
</dl>

Format

Simulated endocrine data. — endosim

A data frame with 2840 observations on the following 4 variables.<dl>
 	<dt><code>gender</code></dt>
<dd>patient's gender. Factor with <code>Male</code> and <code>Female</code> levels.</dd>

 	<dt><code>age</code></dt>
<dd>patient's age.</dd>

 <dt><code>idf_status</code></dt>
<dd>true disease status (presence/absence of two of more cardiovascular risk factors according to the International Diabetes Federation). Numerical vector (0=absence, 1=presence).</dd>

 <dt><code>bmi</code></dt>
<dd>patient's body mass index.</dd>

 
</dl>

endosim: Simulated endocrine data.

Description

Usage

Arguments

Format

References

Examples