  The latent space item response model (LSIRM; Jeon et al., 2021) allows us to
show interactions between respondents and items in item response data by
embedding both items and respondents in a shared and unobserved metric space.
The R package lsirm12pl implements Bayesian estimation of the LSIRM and its
extensions for different response types, base model specifications, and missing
data. Further, the lsirm12pl offers methods to improve model utilization and
interpretation, such as clustering of item positions in an estimated
interaction map. lsirm12pl also provides convenient summary and plotting
options to assess and process estimated results. In this paper, we give an
overview of the methodological basis of LSIRM and describe the LSIRM extensions
considered in the package. We then present the utilization of the package
lsirm12pl with real data examples that are contained in the package.
