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Communications in Statistics - Simulation and Computation Volume 46, 2017 - Issue 3
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Original Articles

Comparison of naïve, Kenward–Roger, and parametric bootstrap interval approaches to small-sample inference in linear mixed models

Vincent S. StaggsHealth Services & Outcomes Research, Children's Mercy Hospitals & Clinics, Kansas City, Missouri, USACorrespondence[email protected]
Pages 1933-1943 | Received 23 Dec 2014, Accepted 10 Feb 2015, Published online: 23 Nov 2016

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Vincent S. Staggs & Keith Feldman. (2023) Use of between-within degrees of freedom as an alternative to the Kenward–Roger method for small-sample inference in generalized linear mixed modeling of clustered count data. Communications in Statistics - Simulation and Computation 52:10, pages 5099-5109.
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Daniel McNeish. (2016) On Using Bayesian Methods to Address Small Sample Problems. Structural Equation Modeling: A Multidisciplinary Journal 23:5, pages 750-773.
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Hatice Tul Kubra AKDUR, Deniz OZONUR & Hulya BAYRAK. (2020) An adaptation of pseudo-score confidence interval method for linear mixed models. Hacettepe Journal of Mathematics and Statistics 49:2, pages 902-913.
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