动物实验的异质性及应对方法。

IF 1.3 4区 农林科学 Q2 VETERINARY SCIENCES Laboratory Animals Pub Date : 2024-10-01 Epub Date: 2024-09-24 DOI:10.1177/00236772241260173
Bernhard Voelkl, Hanno Würbel
{"title":"动物实验的异质性及应对方法。","authors":"Bernhard Voelkl, Hanno Würbel","doi":"10.1177/00236772241260173","DOIUrl":null,"url":null,"abstract":"<p><p>Heterogeneity of study samples is ubiquitous in animal experiments. Here, we discuss the different options of how to deal with heterogeneity in the statistical analysis of a single experiment. Specifically, data from different sub-groups (e.g. sex, strain, age cohorts) may be analysed separately, heterogenization factors may be ignored and data pooled for analysis, or heterogenization factors may be included as additional variables in the statistical model. The cost of ignoring a heterogenization factor is an inflated estimate of the variance and a consequent loss of statistical power. Therefore, it is usually preferable to include the heterogenization factor in the statistical model, especially if the heterogenization factor has been introduced intentionally (e.g. using both sexes). If heterogenization factors are included, they can be treated either as fixed factors in an analysis of variance design or sometimes as random effects in mixed effects regression models. Finally, for an appropriate sample size estimation, it is necessary to decide whether to treat heterogenization factors as nuisance variables, or whether the experiment should be powered to be able to detect not only the main effect of the treatment but also interactions between heterogenization factors and the treatment variable.</p>","PeriodicalId":18013,"journal":{"name":"Laboratory Animals","volume":" ","pages":"493-497"},"PeriodicalIF":1.3000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Heterogeneity of animal experiments and how to deal with it.\",\"authors\":\"Bernhard Voelkl, Hanno Würbel\",\"doi\":\"10.1177/00236772241260173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Heterogeneity of study samples is ubiquitous in animal experiments. Here, we discuss the different options of how to deal with heterogeneity in the statistical analysis of a single experiment. Specifically, data from different sub-groups (e.g. sex, strain, age cohorts) may be analysed separately, heterogenization factors may be ignored and data pooled for analysis, or heterogenization factors may be included as additional variables in the statistical model. The cost of ignoring a heterogenization factor is an inflated estimate of the variance and a consequent loss of statistical power. Therefore, it is usually preferable to include the heterogenization factor in the statistical model, especially if the heterogenization factor has been introduced intentionally (e.g. using both sexes). If heterogenization factors are included, they can be treated either as fixed factors in an analysis of variance design or sometimes as random effects in mixed effects regression models. Finally, for an appropriate sample size estimation, it is necessary to decide whether to treat heterogenization factors as nuisance variables, or whether the experiment should be powered to be able to detect not only the main effect of the treatment but also interactions between heterogenization factors and the treatment variable.</p>\",\"PeriodicalId\":18013,\"journal\":{\"name\":\"Laboratory Animals\",\"volume\":\" \",\"pages\":\"493-497\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Laboratory Animals\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/00236772241260173\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"VETERINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Laboratory Animals","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/00236772241260173","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/24 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"VETERINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

研究样本的异质性在动物实验中无处不在。在此,我们将讨论如何在单个实验的统计分析中处理异质性的不同方案。具体来说,可以分别分析来自不同亚组(如性别、品系、年龄组)的数据,也可以忽略异质性因素,将数据集中起来进行分析,还可以将异质性因素作为额外变量纳入统计模型。忽略异质化因素的代价是夸大方差估计值,从而丧失统计能力。因此,通常最好在统计模型中加入异质化因子,尤其是在有意引入异质化因子的情况下(如使用两性)。如果加入了异质化因子,可以在方差分析设计中将其作为固定因子处理,有时也可以在混合效应回归模型中将其作为随机效应处理。最后,为了估算出适当的样本量,有必要决定是否将异质化因素视为干扰变量,或者是 否应该为实验提供动力,以便不仅能够检测出处理的主要效应,而且能够检测出异质化因素 与处理变量之间的交互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Heterogeneity of animal experiments and how to deal with it.

Heterogeneity of study samples is ubiquitous in animal experiments. Here, we discuss the different options of how to deal with heterogeneity in the statistical analysis of a single experiment. Specifically, data from different sub-groups (e.g. sex, strain, age cohorts) may be analysed separately, heterogenization factors may be ignored and data pooled for analysis, or heterogenization factors may be included as additional variables in the statistical model. The cost of ignoring a heterogenization factor is an inflated estimate of the variance and a consequent loss of statistical power. Therefore, it is usually preferable to include the heterogenization factor in the statistical model, especially if the heterogenization factor has been introduced intentionally (e.g. using both sexes). If heterogenization factors are included, they can be treated either as fixed factors in an analysis of variance design or sometimes as random effects in mixed effects regression models. Finally, for an appropriate sample size estimation, it is necessary to decide whether to treat heterogenization factors as nuisance variables, or whether the experiment should be powered to be able to detect not only the main effect of the treatment but also interactions between heterogenization factors and the treatment variable.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Laboratory Animals
Laboratory Animals 生物-动物学
CiteScore
4.90
自引率
8.30%
发文量
64
审稿时长
6-12 weeks
期刊介绍: The international journal of laboratory animal science and welfare, Laboratory Animals publishes peer-reviewed original papers and reviews on all aspects of the use of animals in biomedical research. The journal promotes improvements in the welfare or well-being of the animals used, it particularly focuses on research that reduces the number of animals used or which replaces animal models with in vitro alternatives.
期刊最新文献
Cardiorespiratory, hemodynamic, and sedative effects of dexmedetomidine in sheep. Management of zoonoses in research institutions - lessons learned from a Coxiella burnetii outbreak case. An innovative approach for health and safety training and occupational health program annual enrollment for laboratory animal care and use personnel. Extended oxygen supplementation after thoracotomy in rats may improve welfare. Animal researchers' views on the publication of negative results and subsequent policy adoptions.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1