set_agg_data

Helper function that aggregates a data set across all participants
and attaches the resulting group-level summary statistics to a
<code>drift_dm_obj</code>. This is required when the user wants to fit aggregated data
(e.g., via the RMSE cost function).

internal

Fit and explore Drift Diffusion Models (DDMs),
a common tool in psychology for describing decision processes in simple
tasks. It can handle both time-independent and time-dependent DDMs. You
either choose prebuilt models or create your own, and the package takes
care of model predictions and parameter estimation. Model predictions
are derived via the numerical solutions provided by Richter, Ulrich, and
Janczyk (2023, <doi:10.1016/j.jmp.2023.102756>).

Valentin Koob

dRiftDM

Estimating (Time-Dependent) Drift Diffusion Models

Thomas Richter

Markus Janczyk

set_agg_data function

<dl><dt>drift_dm_obj</dt>
<dd>a model object (of class <code>drift_dm</code>) to which the
aggregated data will be attached.</dd>
<dt>obs_data_ids</dt>
<dd>a data.frame containing individual-level observations.
Must include an <code>ID</code> column identifying participants.</dd>
<dt>...</dt>
<dd>optional arguments (currently supported are <code>n_bins</code> and
<code>probs</code> which are relevant when using the <code>rmse</code> cost function)</dd></dl>

Arguments

Set aggregated data to a model object — set_agg_data

<dl>

<dt>drift_dm_obj</dt>
<dd>a model object (of class <code>drift_dm</code>) to which the
aggregated data will be attached.</dd>


<dt>obs_data_ids</dt>
<dd>a data.frame containing individual-level observations.
Must include an <code>ID</code> column identifying participants.</dd>


<dt>...</dt>
<dd>optional arguments (currently supported are <code>n_bins</code> and
<code>probs</code> which are relevant when using the <code>rmse</code> cost function)</dd>

</dl>

set_agg_data: Set aggregated data to a model object

Description

Usage

Value

Arguments

Details