theta_av

Compute matrix of theta means over posterior distributions

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

theta_av function

<dl><dt>theta_array</dt>
<dd>An array of dimension (N x d x nsamp/thin) containing posterior samples of respondent latent trait values</dd></dl>

Arguments

Average Thetas — theta_av

<dl>

<dt>theta_array</dt>
<dd>An array of dimension (N x d x nsamp/thin) containing posterior samples of respondent latent trait values</dd>

</dl>

theta_av: Average Thetas

Description

Usage

Value

Arguments