Bae_Luck_2018_data

A dataset with the motion estimation results from Bae &amp; Luck (2018) available from https://osf.io/4m2kb/ (some variables are removed, see the link for the full dataset).

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

Bae_Luck_2018_data function

A data frame with 20480 rows and 8 variables:<dl>
<dt>subject_Num</dt>
<dd>observer ID</dd><dt>trial_Num</dt>
<dd>trial number</dd><dt>TargetDirection</dt>
<dd>true motion direction</dd><dt>RespAngle</dt>
<dd>reported motion direction</dd><dt>motionCoh</dt>
<dd>motion coherence</dd><dt>Block</dt>
<dd>block number</dd><dt>Session</dt>
<dd>session number</dd><dt>err</dt>
<dd>estimation error</dd>
</dl>

Format

Data from a motion estimation task — Bae_Luck_2018_data

A data frame with 20480 rows and 8 variables:<dl>
<dt>subject_Num</dt>
<dd>observer ID</dd>

<dt>trial_Num</dt>
<dd>trial number</dd>

<dt>TargetDirection</dt>
<dd>true motion direction</dd>

<dt>RespAngle</dt>
<dd>reported motion direction</dd>

<dt>motionCoh</dt>
<dd>motion coherence</dd>

<dt>Block</dt>
<dd>block number</dd>

<dt>Session</dt>
<dd>session number</dd>

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


</dl>

Bae_Luck_2018_data: Data from a motion estimation task

Description

Usage

Arguments

Format

References