synth_questions

<p>A synthetic dataset with 3000 rows and 148 questions.
This data replicates the structure of questions following Eurobarometer 94.3 (2021).
It is not intended to be analyzed independently from the vignette.
'</p>

datasets

IRT-M is a semi-supervised approach based on Bayesian Item Response Theory
that produces theoretically identified underlying dimensions from input data
and a constraints matrix. The methodology is fully described in 'Morucci et al. (2024),
"Measurement That Matches Theory: Theory-Driven Identification in Item Response Theory Models"'.
Details are available at <https://www.cambridge.org/core/journals/american-political-science-review/article/measurement-that-matches-theory-theorydriven-identification-in-item-response-theory-models/395DA1DFE3DCD7B866DC053D7554A30B>.

Margaret Foster

IRTM

Theory-Driven Item Response Theory (IRT) Models

Marco Morucci

David Siegel

synth_questions function

<p>A data frame with 3000 rows and 148 columns representing synthetic survey responses</p>

synth_questions: Questions for the Synthetic European sentiment survey in the vignette

Description

Arguments

Format