obs_data

An observed dataset from a hypothetical PK model. Altered to include NTIME, GROUP, GENDER.

datasets

Perform a Visual Predictive Check (VPC), while accounting for
stratification, censoring, and prediction correction. Using piping from
'magrittr', the intuitive syntax gives users a flexible and powerful method
to generate VPCs using both traditional binning and a new binless approach
Jamsen et al. (2018) <doi:10.1002/psp4.12319> with Additive Quantile
Regression (AQR) and Locally Estimated Scatterplot Smoothing (LOESS)
prediction correction.

James Craig

tidyvpc

VPC Percentiles and Prediction Intervals

Olivier Barriere

Benjamin Rich

Samer Mouksassi

Kris Jamsen

obs_data function

A data frame with 600 rows and 7 variables:<dl class="dl-horizontal">
 <dt>ID</dt><dd>Subect identifier</dd>
 <dt>TIME</dt><dd>Time</dd>
 <dt>DV</dt><dd>Concentration of drug</dd>
 <dt>AMT</dt><dd>Amount of dosage initially administered at DV = 0, TIME = 0</dd>
 <dt>DOSE</dt><dd>Dosage amount</dd>
 <dt>MDV</dt><dd>Dummy indiciating missing dependent variable value</dd>
 <dt>NTIME</dt><dd>Nominal Time</dd>
 <dt>GENDER</dt><dd>Character variable indicating subject's gender ("M", "F")</dd>
 <dt>STUDY</dt><dd>Character variable indicating study type ("Study A", "Study B")</dd>
</dl>

Format

Example observed data from vpc package. — obs_data

A data frame with 600 rows and 7 variables:<dl class='dl-horizontal'>
 <dt>ID</dt><dd>Subect identifier</dd>
 <dt>TIME</dt><dd>Time</dd>
 <dt>DV</dt><dd>Concentration of drug</dd>
 <dt>AMT</dt><dd>Amount of dosage initially administered at DV = 0, TIME = 0</dd>
 <dt>DOSE</dt><dd>Dosage amount</dd>
 <dt>MDV</dt><dd>Dummy indiciating missing dependent variable value</dd>
 <dt>NTIME</dt><dd>Nominal Time</dd>
 <dt>GENDER</dt><dd>Character variable indicating subject's gender ("M", "F")</dd>
 <dt>STUDY</dt><dd>Character variable indicating study type ("Study A", "Study B")</dd>
</dl>

obs_data: Example observed data from vpc package.

Description

Usage

Arguments

Format