Gibbs Samplers for Logistic Item Response Models via the Pólya–Gamma Distribution: A Computationally Efficient Data-Augmentation Strategy
Crossref DOI link: https://doi.org/10.1007/s11336-018-9641-x
Published Online: 2018-10-31
Published Print: 2019-06
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Jiang, Zhehan http://orcid.org/0000-0002-1376-9439
Templin, Jonathan
Text and Data Mining valid from 2018-10-31
Article History
Received: 24 October 2017
First Online: 31 October 2018