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Sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers

The availability of sexed day-old broiler chicks is becoming an issue as feather sexing is no longer possible. This has great implications for broiler researchers as the use of randomly distributed mixed-sex birds may result in a greater between-pen variation and thus less statistical power than the...

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Autores principales: England, Ashley D., Musigwa, Sosthene, Kumar, Alip, Daneshmand, Ali, Gharib-Naseri, Kosar, Kheravii, Sarbast K., Pesti, Gene, Wu, Shu-Biao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857968/
https://www.ncbi.nlm.nih.gov/pubmed/36662683
http://dx.doi.org/10.1371/journal.pone.0280040
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author England, Ashley D.
Musigwa, Sosthene
Kumar, Alip
Daneshmand, Ali
Gharib-Naseri, Kosar
Kheravii, Sarbast K.
Pesti, Gene
Wu, Shu-Biao
author_facet England, Ashley D.
Musigwa, Sosthene
Kumar, Alip
Daneshmand, Ali
Gharib-Naseri, Kosar
Kheravii, Sarbast K.
Pesti, Gene
Wu, Shu-Biao
author_sort England, Ashley D.
collection PubMed
description The availability of sexed day-old broiler chicks is becoming an issue as feather sexing is no longer possible. This has great implications for broiler researchers as the use of randomly distributed mixed-sex birds may result in a greater between-pen variation and thus less statistical power than the use of single-sex birds. The objective of this study was to evaluate the effect of including sex proportion as a covariate in an analysis of covariance (ANCOVA) on the statistical power compared to analysis of variance (ANOVA) where sex was not considered. The statistical parameters examined include mean square error (MSE), the F-statistic, model fit, model significance and observed power. A total of 4 separate experiments that used mixed-sex broilers with unequal numbers of male and female birds per pen were conducted during which performance of the birds was measured. The male % in each pen was recorded during each experiment and corrected for mortality. The performance results were analysed by ANOVA and the statistical parameters were then compared to ANCOVA where sex proportion was included as a covariate. The results showed that a set of assumptions first needed to be met to run ANCOVA. In addition, if the ANOVA results show a high level of model significance and power, then ANCOVA may not be necessary. In other circumstances where the assumptions are met and model significance and observed power are low, the inclusion of sex proportion as a covariate in the analysis will help to reduce MSE, increase the F-statistic value and improve the model significance, model fit and observed power. Therefore, it is suggested that sex proportion should be considered as a covariate in ANCOVA to improve statistical power in nutritional experiments when male and female broilers are unequally and randomly distributed in pens.
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spelling pubmed-98579682023-01-21 Sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers England, Ashley D. Musigwa, Sosthene Kumar, Alip Daneshmand, Ali Gharib-Naseri, Kosar Kheravii, Sarbast K. Pesti, Gene Wu, Shu-Biao PLoS One Research Article The availability of sexed day-old broiler chicks is becoming an issue as feather sexing is no longer possible. This has great implications for broiler researchers as the use of randomly distributed mixed-sex birds may result in a greater between-pen variation and thus less statistical power than the use of single-sex birds. The objective of this study was to evaluate the effect of including sex proportion as a covariate in an analysis of covariance (ANCOVA) on the statistical power compared to analysis of variance (ANOVA) where sex was not considered. The statistical parameters examined include mean square error (MSE), the F-statistic, model fit, model significance and observed power. A total of 4 separate experiments that used mixed-sex broilers with unequal numbers of male and female birds per pen were conducted during which performance of the birds was measured. The male % in each pen was recorded during each experiment and corrected for mortality. The performance results were analysed by ANOVA and the statistical parameters were then compared to ANCOVA where sex proportion was included as a covariate. The results showed that a set of assumptions first needed to be met to run ANCOVA. In addition, if the ANOVA results show a high level of model significance and power, then ANCOVA may not be necessary. In other circumstances where the assumptions are met and model significance and observed power are low, the inclusion of sex proportion as a covariate in the analysis will help to reduce MSE, increase the F-statistic value and improve the model significance, model fit and observed power. Therefore, it is suggested that sex proportion should be considered as a covariate in ANCOVA to improve statistical power in nutritional experiments when male and female broilers are unequally and randomly distributed in pens. Public Library of Science 2023-01-20 /pmc/articles/PMC9857968/ /pubmed/36662683 http://dx.doi.org/10.1371/journal.pone.0280040 Text en © 2023 England et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
England, Ashley D.
Musigwa, Sosthene
Kumar, Alip
Daneshmand, Ali
Gharib-Naseri, Kosar
Kheravii, Sarbast K.
Pesti, Gene
Wu, Shu-Biao
Sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers
title Sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers
title_full Sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers
title_fullStr Sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers
title_full_unstemmed Sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers
title_short Sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers
title_sort sex proportion as a covariate increases the statistical test power in growth performance based experiments using as-hatched broilers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857968/
https://www.ncbi.nlm.nih.gov/pubmed/36662683
http://dx.doi.org/10.1371/journal.pone.0280040
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