Stochastic Approximation Methods for Latent Regression Item Response Models

By Matthias von Davier, Sandip Sinharay. 2010

49 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a3432f5232d0d56b8245ef0038c19f6d9e0898aa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Li Cai
2. Jerome P. Reiter
3. S. Reise
4. R. Chalmers
5. Dennis A. Revicki

In Management Science and Operations Research

1. Yajuan Si
2. Li Cai
3. Jerome P. Reiter
4. S. Reise
5. Josep Domingo-Ferrer
6. R. Chalmers
7. Dennis A. Revicki
8. Kristian Lum

In Statistics and Probability

1. Yajuan Si
2. Li Cai
3. Jerome P. Reiter
4. Joerg Drechsler

Citations in the corpus

• Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis (2010, methodology): “A general convergence result was given by Cai (2008a), and von Davier and Sinharay (2010) applied a version of MH-RM algorithm to estimate a multidimensional latent regression IRT model heavily relied upon in scaling National Assessment of Educational Progress (NAEP) data (see von Davier &…”
• Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys (2013, background): “Such background variables are central for data analysis, modeling, and policy research (Ballou, Sanders, & Wright, 2004; Thomas, 2002; von Davier & Sinharay, 2007, 2010).”