clmm_maximal

Fitted Cumulative Link Mixed Model for Nadarevic and Erdfelder Data

datasets

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

Illusory Truth Longitudinal Study

Emma Henderson

clmm_maximal function

An object of class "clmm", resulting from a call to the
<code><a rd-options="ordinal" href="/link/clmm?package=truthiness&version=1.2.5&to=ordinal" data-mini-rdoc="ordinal::clmm">clmm</a></code> function.

Format

Fitted Cumulative Link Mixed Model for Nadarevic and Erdfelder Data — clmm_maximal

An object of class "clmm", resulting from a call to the
<code><a rd-options='ordinal' href='clmm'>clmm</a></code> function.

clmm_maximal: Fitted Cumulative Link Mixed Model for Nadarevic and Erdfelder Data

Description

Usage

Arguments

Format

Details

See Also