Experiences With Markov Chain Monte Carlo Convergence Assessment in Two Psychometric Examples

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Bayesian analyses : where to start and what to report (2014, background): “A variety of statistical tools can be used to help monitor and evaluate chain convergence (see, Sinharay, 2004), and visual inspection of convergence plots can also aid in detecting non-convergence.”
Recovery of Graded Response Model Parameters (2012, background): “However, convergence assessment of Markov chains remains a difficult subject (see, for example, Sinharay, 2004).”
A Mixture Rasch Model With Item Response Time Components (2010, unknown): “Sinharay (2004) recommended the use of the MPSRF because of its apparent sensitivity to lack of convergence.”
Skills Diagnosis Using IRT-Based Latent Class Models (2007, background): “Sinharay (2004) reviews state-of-the-art techniques for convergence checking in”
The fusion model skills diagnosis system (2007, background): “The reader is referred to Cowles and Carlin (1996) and a recent article by Sinharay (2004) for an excellent and thorough discussion.”
Improving Transparency and Replication in Bayesian Statistics: The WAMBS-Checklist (2017, unknown): “Although Sinharay (2004) and others (see, e.g., Brooks & Roberts, 1998) discuss several diagnostic tools to determine convergence, there is no consensus which statistical criterion can be considered as the “best” one.”