log_mixed_data

A dataset containing the minimum required variables needed to input data
into the GrowthCurveME package functions

datasets

Simple and user-friendly wrappers to the 'saemix' package for
performing linear and non-linear mixed-effects regression modeling for
growth data to account for clustering or longitudinal analysis via repeated
measurements. The package allows users to fit a variety of growth
models, including linear, exponential, logistic, and 'Gompertz'
functions. For non-linear models, starting values are automatically
calculated using initial least-squares estimates. The package includes
functions for summarizing models, visualizing data and results,
calculating doubling time and other key statistics, and generating model
diagnostic plots and residual summary statistics. It also provides
functions for generating publication-ready summary tables for reports.
Additionally, users can fit linear and non-linear least-squares
regression models if clustering is not applicable. The mixed-effects
modeling methods in this package are based on Comets, Lavenu, and
Lavielle (2017) <doi:10.18637/jss.v080.i03> as implemented in the
'saemix' package. Please contact us at models@dfci.harvard.edu
with any questions.

Anand Panigrahy

GrowthCurveME

Mixed-Effects Modeling for Growth Data

Sonam Bhatia

Thomas Quinn

Aniket Shetty

Keith Ligon

Center for Patient-Derived Models Dana-Farber Cancer Institute

log_mixed_data function

A data frame with 800 rows and 3 variables:<dl>
<dt>cluster</dt>
<dd>A character type variable used to specify the clustering
of values by a particular metric. Note even when selecting a least-squares,
do not leave this variable NA or empty. Instead fill in these values with
a single repetitive dummy variable (e.g., '1') for the package to
run properly</dd><dt>time</dt>
<dd>A numeric type variable for any measurement in time such as
minutes, hours, or days</dd><dt>growth_metric</dt>
<dd>A numeric type variable for measuring growth such as
confluency or cell count</dd>
</dl>

Format

Sample logistic growth dataset — log_mixed_data

A data frame with 800 rows and 3 variables:<dl>
<dt>cluster</dt>
<dd>A character type variable used to specify the clustering
of values by a particular metric. Note even when selecting a least-squares,
do not leave this variable NA or empty. Instead fill in these values with
a single repetitive dummy variable (e.g., '1') for the package to
run properly</dd>

<dt>time</dt>
<dd>A numeric type variable for any measurement in time such as
minutes, hours, or days</dd>

<dt>growth_metric</dt>
<dd>A numeric type variable for measuring growth such as
confluency or cell count</dd>


</dl>

log_mixed_data: Sample logistic growth dataset

Description

Usage

Arguments

Format

Examples