diabetes

This dataset contains simulated medical measurements for Diabetes and is
emulated after data from the Diabetes Prevention Program.
Each column represents change in a key metabolic indicators after two years for the placebo group
receiving no treatment.

datasets

Implements nonparametric bootstrap tests for detecting monotonicity
in regression functions from Hall, P. and Heckman, N. (2000) <doi:10.1214/aos/1016120363>
Includes tools for visualizing results using Nadaraya-Watson kernel regression and supports
efficient computation with 'C++'. Tutorials and shiny application demo are
available at <https://www.laylaparast.com/monotonicitytest> and <https://parastlab.shinyapps.io/MonotonicityTest>.

Dylan Huynh

MonotonicityTest

Nonparametric Bootstrap Test for Regression Monotonicity

diabetes function

A data frame with 1000 rows and 4 variables:<dl>
 <dt>CLDL</dt>
<dd>Change in low-density lipoprotein (LDL) cholesterol (mg/dL).</dd> <dt>GLUCOSE</dt>
<dd>Change in fasting plasma glucose levels (mg/dL).</dd> <dt>TRIG</dt>
<dd>Change in triglyceride levels (mg/dL).</dd> <dt>HBA1C</dt>
<dd>Change in hemoglobin A1c levels (%).</dd>
</dl>

Format

A Simulated Diabetes Dataset — diabetes

A data frame with 1000 rows and 4 variables:<dl>
 <dt>CLDL</dt>
<dd>Change in low-density lipoprotein (LDL) cholesterol (mg/dL).</dd>

 <dt>GLUCOSE</dt>
<dd>Change in fasting plasma glucose levels (mg/dL).</dd>

 <dt>TRIG</dt>
<dd>Change in triglyceride levels (mg/dL).</dd>

 <dt>HBA1C</dt>
<dd>Change in hemoglobin A1c levels (%).</dd>


</dl>

diabetes: A Simulated Diabetes Dataset

Description

Usage

Arguments

Format

Examples