Linear Mixed Effect Models for Rehabilitation Research
- PMID: 34561354
- DOI: 10.1097/PHM.0000000000001888
Linear Mixed Effect Models for Rehabilitation Research
Abstract
The growing emphasis on evidence-based methods in rehabilitation medicine calls for increase in the sophistication of study design and analytic methods across the discipline. To properly evaluate new treatment options, a physiatrist needs to be able to separate treatment effects from parallel changes that occur over time and variations that may be due to subject demographics. Simple t tests may not be appropriate where observations may vary randomly across different institutions participating in a multicenter trial, or the same rehabilitation course may lead to different outcomes because of various factors. In the analysis of any rehabilitation program, these random variations must be accounted for to receive accurate results. In this short review, we focus in one of the most common approaches that are appropriate to account for these variations, namely, linear mixed effect models.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
Conflict of interest statement
Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.
References
-
- Cicerone KD, Dahlberg C, Kalmar K, et al.: Evidence-based cognitive rehabilitation: recommendations for clinical practice. Arch Phys Med Rehabil 2000;81:1596–615
-
- Cicerone KD, Goldin Y, Ganci K, et al.: Evidence-based cognitive rehabilitation: systematic review of the literature from 2009 through 2014. Arch Phys Med Rehabil 2019;100:1515–33
-
- Hart T, Bagiella E: Design and implementation of clinical trials in rehabilitation research. Arch Phys Med Rehabil 2012;93(suppl 8):S117–26
-
- Park NW, Ingles JL: Effectiveness of attention rehabilitation after an acquired brain injury: a meta-analysis. Neuropsychology 2001;15:199–210
-
- West BT, Welch KB, Gałecki AT, et al.: Linear Mixed Models: A Practical Guide Using Statistical Software , 2nd ed. Boca Raton, CRC Press, Taylor & Francis Group, 2015
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