ntp_polyk

Poly-k test
This function implements the NTP's polyK trend test.

Toxicology routines for analyzing dose-response data include dose-response analysis
and trend tests. Dose-Response methods are based upon the US EPA's benchmark dose software 3. Methods have
been extended to include additional functionality based on World Health Organization
guidelines. It further supports the European Food Safety Authority's
draft guidance on model averaging. The dose-response methods and datasets used in this package are
described in Wheeler et al. (2019) <doi:10.1111/risa.13218>, Wheeler et al. (2020) <doi:10.1111/risa.13537>,
and Wheeler et al. (2022) <doi:10.1002/env.2728>. NTP routines are described in
Bailer and Portier (1988) <doi:10.2307/2531856>, Bieler and Williams (1993) <doi:10.2307/2532200>,
Williams (1971) <doi:10.2307/2528930>, and Shirley (1977) <doi:10.2307/2529789>.

Matt Wheeler

ToxicR

Analyzing Toxicology Dose-Response Data

Sooyeong Lim

Eric Wimberly

Keith Shockley

Jennifer Fostel

Lonlong Yang

Dawan Taley

Cari Martini

Ashwin Raghuraman

Steven Johnson

Aymeric Stamm

Dirk Eddelbuettel

U.S. Deptartment of Health and Human Services (US HHS), National Institute of Environmental Health Sciences (NIEHS) 

ntp_polyk function

<dl><dt>dose</dt>
<dd>An equation of the form \(Y \sim X.\) Here the variable
\(Y\) is the response of interest, and \(X\) represents discrete experimental 
conditions. For example, if weight is the dependent variable, and you are
interested in looking at the trend across sex one would have 'weight ~ sex'.</dd>
<dt>tumor</dt>
<dd>A data frame with column names in the formula.</dd>
<dt>daysOnStudy</dt>
<dd>The name of the variable containing the doses in the data frame \(data\).
It is expected multiple doses for each of the experimental conditions \(X\).</dd></dl>

Arguments

Poly-k test
This function implements the NTP's polyK trend test. — ntp_polyk

<dl>

<dt>dose</dt>
<dd>An equation of the form \(Y \sim X.\) Here the variable
\(Y\) is the response of interest, and \(X\) represents discrete experimental 
conditions. For example, if weight is the dependent variable, and you are
interested in looking at the trend across sex one would have 'weight ~ sex'.</dd>


<dt>tumor</dt>
<dd>A data frame with column names in the formula.</dd>


<dt>daysOnStudy</dt>
<dd>The name of the variable containing the doses in the data frame \(data\).
It is expected multiple doses for each of the experimental conditions \(X\).</dd>

</dl>

Poly-k test
This function implements the NTP's polyK trend test.

ntp_polyk: Poly-k test This function implements the NTP's polyK trend test.

Description

Usage

Value

Arguments

Examples