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dc.contributor.authorStewart, Sen_NZ
dc.contributor.authorPearson, Jen_NZ
dc.contributor.authorRome, Ken_NZ
dc.contributor.authorDalbeth, Nen_NZ
dc.contributor.authorVandal, Aen_NZ
dc.date.accessioned2017-10-18T03:09:08Z
dc.date.available2017-10-18T03:09:08Z
dc.date.copyright2017-10-16en_NZ
dc.identifier.citationGait & Posture, Volume 59, Pp. 182–187
dc.identifier.urihttp://hdl.handle.net/10292/10880
dc.description.abstractObjectives Statistical techniques currently used in musculoskeletal research often inefficiently account for paired-limb measurements or the relationship between measurements taken from multiple regions within limbs. This study compared three commonly used analysis methods with a mixed-models approach that appropriately accounted for the association between limbs, regions, and trials and that utilised all information available from repeated trials. Method Four analysis were applied to an existing data set containing plantar pressure data, which was collected for seven masked regions on right and left feet, over three trials, across three participant groups. Methods 1–3 averaged data over trials and analysed right foot data (Method 1), data from a randomly selected foot (Method 2), and averaged right and left foot data (Method 3). Method 4 used all available data in a mixed-effects regression that accounted for repeated measures taken for each foot, foot region and trial. Confidence interval widths for the mean differences between groups for each foot region were used as a criterion for comparison of statistical efficiency. Results Mean differences in pressure between groups were similar across methods for each foot region, while the confidence interval widths were consistently smaller for Method 4. Method 4 also revealed significant between-group differences that were not detected by Methods 1–3. Conclusion A mixed effects linear model approach generates improved efficiency and power by producing more precise estimates compared to alternative approaches that discard information in the process of accounting for paired-limb measurements. This approach is recommended in generating more clinically sound and statistically efficient research outputs.
dc.publisherElsevier
dc.relation.urihttp://www.sciencedirect.com/science/article/pii/S0966636217309748
dc.rightsCopyright © 2017 Elsevier Ltd. All rights reserved. This is the author’s version of a work that was accepted for publication in (see Citation). Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. The definitive version was published in (see Citation). The original publication is available at (see Publisher's Version).
dc.subjectPlantar pressure; Gait; Statistical analysis; Lower limb; Foot; Mixed effects models; Statistical efficiency
dc.titleAnalysis of Data Collected From Right and Left Limbs: Accounting for Dependence and Improving Statistical Efficiency in Musculoskeletal Researchen_NZ
dc.typeJournal Article
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.1016/j.gaitpost.2017.10.018
pubs.elements-id314946
aut.relation.journalGait and Postureen_NZ


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