Reporting and analysis of repeated measurements in preclinical animals experiments

dc.contributor.author Zhao, Jing
dc.contributor.author O'Connor, Annette
dc.contributor.author Totton, Sarah
dc.contributor.author Wang, Chong
dc.contributor.author Cullen, Jonah
dc.contributor.department Statistics
dc.contributor.department Veterinary Diagnostic and Production Animal Medicine
dc.date 2019-09-19T04:53:19.000
dc.date.accessioned 2020-07-07T05:12:49Z
dc.date.available 2020-07-07T05:12:49Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2019
dc.date.issued 2019-08-12
dc.description.abstract <p>A common feature of preclinical animal experiments is repeated measurement of the outcome, e.g., body weight measured in mice pups weekly for 20 weeks. Separate time point analysis or repeated measures analysis approaches can be used to analyze such data. Each approach requires assumptions about the underlying data and violations of these assumptions have implications for estimation of precision, and type I and type II error rates. Given the ethical responsibilities to maximize valid results obtained from animals used in research, our objective was to evaluate approaches to reporting repeated measures design used by investigators and to assess how assumptions about variation in the outcome over time impact type I and II error rates and precision of estimates. We assessed the reporting of repeated measures designs of 58 studies in preclinical animal experiments. We used simulation modelling to evaluate three approaches to statistical analysis of repeated measurement data. In particular, we assessed the impact of (a) repeated measure analysis assuming that the outcome had non-constant variation at all time points (heterogeneous variance) (b) repeated measure analysis assuming constant variation in the outcome (homogeneous variance), (c) separate ANOVA at individual time point in repeated measures designs. The evaluation of the three model fitting was based on comparing the p-values distributions, the type I and type II error rates and by implication, the shrinkage or inflation of standard error estimates from 1000 simulated dataset. Of 58 studies with repeated measures design, three provided a rationale for repeated measurement and 23 studies reported using a repeated-measures analysis approach. Of the 35 studies that did not use repeated-measures analysis, fourteen studies used only two time points to calculate weight change which potentially means collected data was not fully utilized. Other studies reported only select time points (<em>n</em> = 12) raising the issue of selective reporting. Simulation studies showed that an incorrect assumption about the variance structure resulted in modified error rates and precision estimates. The reporting of the validity of assumptions for repeated measurement data is very poor. The homogeneous variation assumption, which is often invalid for body weight measurements, should be confirmed prior to conducting the repeated-measures analysis using homogeneous covariance structure and adjusting the analysis using corrections or model specifications if this is not met.</p>
dc.description.comments <p>This article is published as Zhao, Jing, Chong Wang, Sarah C. Totton, Jonah N. Cullen, and Annette M. O’Connor. "Reporting and analysis of repeated measurements in preclinical animals experiments." <em>PLOS One </em>14, no. 8 (2019): e0220879. DOI: <a href="http://dx.doi.org/10.1371/journal.pone.0220879" target="_blank">10.1371/journal.pone.0220879</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/vdpam_pubs/138/
dc.identifier.articleid 1141
dc.identifier.contextkey 15164794
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath vdpam_pubs/138
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/91981
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/vdpam_pubs/138/2019_OConnorAnnette_ReportingAnalysis.pdf|||Fri Jan 14 20:01:36 UTC 2022
dc.source.uri 10.1371/journal.pone.0220879
dc.subject.disciplines Clinical Trials
dc.subject.disciplines Design of Experiments and Sample Surveys
dc.subject.disciplines Veterinary Medicine
dc.title Reporting and analysis of repeated measurements in preclinical animals experiments
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication bbd2db96-9105-4b96-8f96-713be18a75ac
relation.isAuthorOfPublication b715071c-c3bd-419c-b021-0ac4702f346a
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
relation.isOrgUnitOfPublication 5ab07352-4171-4f53-bbd7-ac5d616f7aa8
File
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
2019_OConnorAnnette_ReportingAnalysis.pdf
Size:
1.53 MB
Format:
Adobe Portable Document Format
Description:
Collections