Randomly generated demographic data domain

datasets

Automated methods to assemble population PK (pharmacokinetic) and
PKPD (pharmacodynamic) datasets for analysis in 'NONMEM' (non-linear mixed effects
modeling) by Bauer (2019) <doi:10.1002/psp4.12404>. The package includes functions
to build datasets from SDTM (study data tabulation module)
<https://www.cdisc.org/standards/foundational/sdtm>, ADaM (analysis dataset
module) <https://www.cdisc.org/standards/foundational/adam>, or other dataset
formats. The package will combine population datasets, add covariates, and
create documentation to support regulatory submission and internal communication.

Stephen Amori

apmx

Automated Population Pharmacokinetic Dataset Assembly

Ethan DellaMaestra

Michael Dick

Daniel Litow

Jonah Lyon

DM function

## `DM`
A data frame with 22 rows and 12 variables:<dl>
 <dt>STUDYID</dt>
<dd>study label</dd> <dt>SITEID</dt>
<dd>site code</dd> <dt>SUBJID</dt>
<dd>subject code</dd> <dt>USUBJID</dt>
<dd>unique subject ID</dd> <dt>SCRFL</dt>
<dd>screen fail flag</dd> <dt>ICFDT</dt>
<dd>informed consent date</dd> <dt>ICFDTC</dt>
<dd>informed consent date character form</dd> <dt>DOBDT</dt>
<dd>date of birth</dd> <dt>AGE</dt>
<dd>subject baseline age</dd> <dt>SEX</dt>
<dd>subject sex</dd> <dt>RACE</dt>
<dd>subject race</dd> <dt>ETHNIC</dt>
<dd>subject ethnicity</dd>
</dl>

Format

DM — DM

## `DM`
A data frame with 22 rows and 12 variables:<dl>
 <dt>STUDYID</dt>
<dd>study label</dd>

 <dt>SITEID</dt>
<dd>site code</dd>

 <dt>SUBJID</dt>
<dd>subject code</dd>

 <dt>USUBJID</dt>
<dd>unique subject ID</dd>

 <dt>SCRFL</dt>
<dd>screen fail flag</dd>

 <dt>ICFDT</dt>
<dd>informed consent date</dd>

 <dt>ICFDTC</dt>
<dd>informed consent date character form</dd>

 <dt>DOBDT</dt>
<dd>date of birth</dd>

 <dt>AGE</dt>
<dd>subject baseline age</dd>

 <dt>SEX</dt>
<dd>subject sex</dd>

 <dt>RACE</dt>
<dd>subject race</dd>

 <dt>ETHNIC</dt>
<dd>subject ethnicity</dd>


</dl>

DM: DM

Description

Usage

Arguments

Format