Pascucci_et_al_2019_data

A dataset with the orientation estimation results from Experiment 2 in Pascucci et al. (2019) available from https://doi.org/10.5281/zenodo.2544946.

datasets

Light-weight functions for computing descriptive statistics in different circular spaces (e.g., 2pi, 180, or 360 degrees), to handle angle-dependent biases, pad circular data, and more. Specifically aimed for psychologists and neuroscientists analyzing circular data. Basic methods are based on Jammalamadaka and SenGupta (2001) <doi:10.1142/4031>, removal of cardinal biases is based on the approach introduced in van Bergen, Ma, Pratte, & Jehee (2015) <doi:10.1038/nn.4150> and Chetverikov and Jehee (2023) <doi:10.1038/s41467-023-43251-w>.

Andrey Chetverikov

circhelp

Circular Analyses Helper Functions

Eline Van Geert

Pascucci_et_al_2019_data function

A data frame with 4400 rows and 5 variables:<dl>
<dt>observer</dt>
<dd>observer ID</dd><dt>orientation</dt>
<dd>true orientation</dd><dt>reported</dt>
<dd>reported orientation</dd><dt>rt</dt>
<dd>response time</dd><dt>err</dt>
<dd>estimation error</dd>
</dl>

Format

Data from an orientation estimation task — Pascucci_et_al_2019_data

A data frame with 4400 rows and 5 variables:<dl>
<dt>observer</dt>
<dd>observer ID</dd>

<dt>orientation</dt>
<dd>true orientation</dd>

<dt>reported</dt>
<dd>reported orientation</dd>

<dt>rt</dt>
<dd>response time</dd>

<dt>err</dt>
<dd>estimation error</dd>


</dl>

Pascucci_et_al_2019_data: Data from an orientation estimation task

Description

Usage

Arguments

Format

References