get_avg_trials

internal helper — assumes each <code>ID</code> appears with the same set of conditions
in column <code>Cond</code>. counts trials per <code>ID</code>×<code>Cond</code> and averages across <code>ID</code>.

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

get_avg_trials function

<dl><dt>obs_data_ids</dt>
<dd>data frame with columns <code>ID</code> and <code>Cond</code>; one row per
trial.</dd></dl>

Arguments

Compute average trials per condition across individuals — get_avg_trials

<dl>

<dt>obs_data_ids</dt>
<dd>data frame with columns <code>ID</code> and <code>Cond</code>; one row per
trial.</dd>

</dl>

get_avg_trials: Compute average trials per condition across individuals

Description

Usage

Value

Arguments