simulate_category_guess

nruns

<p>Run simulations tabulating the number of correct guesses assuming a
participant is just guessing during the categorization task. This
can be used to estimate a chance baseline on the 64 categorization
trials.</p>

Data and functions for analyzing and simulating illusory
truth datasets, developed as part of a longitudinal study by
Henderson, Barr, and Simons (2020). The illusory truth effect is
the observation that people rate repeated statements as more
likely to be true than novel statements. We tested the trajectory
of the illusory truth effect by collecting truth ratings for
statements repeated across four time intervals: immediately, one
day, one week, and one month following initial presentation. The
package contains the anonymized data from the study along with
stimulus materials, as well as functions for analyzing the data,
running simulations, and calculating power. Further details about
the project are available at <https://osf.io/nvugt/>, which
includes Stage 1 of the Registered Report at the Journal of
Cognition (<https://osf.io/vqnx2/>).

Dale Barr

truthiness

simulate_category_guess: Simulate Guessing During the Categorization Task

Description

Usage

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Examples