ds_gng

The Go/No Go is a task in which participants respond to one set of stimuli, but withhold a response
to another set of stimuli. This particular dataset is from the first session of a study that is 
described in detail in 10.1016/j.tate.2019.102887Hedge, Powell, and Sumner (2018). 
It was graciously provided by <a href="https://www.researchgate.net/profile/Craig-Hedge">Craig Hedge</a> and can
be obtained from <a href="https://osf.io/cwzds">https://osf.io/cwzds</a>.

datasets

Estimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaires. The 'splithalfr' supports researcher-provided scoring algorithms, with six vignettes illustrating how on included datasets. The package provides four splitting methods (first-second, odd-even, permutated, Monte Carlo), the option to stratify splits by task design, a number of reliability coefficients, and the option to sub-sample data.

Thomas Pronk

splithalfr

Estimate Split-Half Reliabilities

ds_gng function

An object of class <code>data.frame</code> with 28200 rows and 7 columns.

Format

The Go/No Go is a task in which participants respond to one set of stimuli, but withhold a response
to another set of stimuli. This particular dataset is from the first session of a study that is 
described in detail in 10.1016/j.tate.2019.102887Hedge, Powell, and Sumner (2018). 
It was graciously provided by <a href='https://www.researchgate.net/profile/Craig-Hedge'>Craig Hedge</a> and can
be obtained from <a href='https://osf.io/cwzds'>https://osf.io/cwzds</a>.

ds_gng: Example Go/No Go data

Description

Usage

Arguments

Format

Details