Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis

By Li Cai. 2010

250 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Social Psychology

View Paper: https://www.semanticscholar.org/paper/f34f796613708c02aeeb0bd58b801b5607bfa25a

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. R. Chalmers
2. N. Rose
3. Linda Gräfe
4. Dennis A. Revicki
5. S. Pohl
6. S. Reise
7. Alexandre J. S. Morin
8. Herbert W. Marsh

In Management Science and Operations Research

1. Linda Gräfe
2. S. Pohl
3. R. Chalmers
4. N. Rose
5. Dennis A. Revicki
6. S. Reise
7. Alexandre J. S. Morin
8. Herbert W. Marsh

In Social Psychology

1. R. Chalmers
2. Dennis A. Revicki
3. S. Reise

Citations in the corpus

• Dealing With Omitted and Not-Reached Items in Competence Tests (2014, background): “The latent approaches for modeling missing responses may result in estimation problems (see, e.g., Cai, 2010), especially when the sample size and the number of missing responses are rather small or when both the latent ability and the latent response propensity are multidimensional (Rose, 2013;…”
• The Rediscovery of Bifactor Measurement Models (2012, methodology): “Only recently have highly efficient dimensionality reduction techniques become available (Cai, 2010a, 2010b, 2010c) that greatly expand the Note.”
• mirt: A Multidimensional Item Response Theory Package for the R Environment (2012, methodology): “The bifactor model can specify only one additional item specific factor (although see Cai 2010c), but is not limited in the number of factors estimated since the quadratures remain fixed regardless of the number of specific factors extracted.”
• Item Response Theory—A Statistical Framework for Educational and Psychological Measurement (2021, unknown): “These algorithms avoid the numerical integration by Monte Carlo simulation (Cai, 2010a,b; Diebolt and Ip, 1996; Ip, 2002b; Meng and Schilling, 1996; Zhang et al., 2020; Zhang and Chen, 2020).”
• Handbook of Item Response Theory Modeling : Applications to Typical Performance Assessment (2014, methodology): “Cai (2010a) noted that instead of treating the Monte Carlo noise as a nuisance to be contained, it may in fact be employed more productively.”