John W. Green, Manousos Foudoulakis, Timothy Fredricks, Thomas Bean, Jonathan Maul, Stephanie Plautz, Pablo Valverde, Adam Schapaugh, Xiaoyi Sopko, Zhenglei Gao
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We present benefits and limitations of this BMD approach for older studies being re-evaluated and for new studies designed for with BMD analysis anticipated. Model averaging is recommended as preferable to model selection for BMD analysis. Even for a new study following the modified experimental design analyses, with BMD methodology will only be possible for a restricted set of response variables. The judicious use of historical control data, identification of outlier data points, increased use of distributions more consistent with the nature of the data collected as opposed to forcing normality-based methods, and trend-based hypothesis tests are shown to be effective for many studies, but limitations on their applicability are also recognized and explained. Updated statistical methodologies are illustrated with case studies conducted under existing regulatory guidelines that have been submitted for product registrations. Through the adoption of alternative avian reproduction study design elements combined with the suggested revised statistical methodologies the conduct, analyses, and utility of avian reproduction studies for avian risk assessments can be improved.</p></div>","PeriodicalId":54293,"journal":{"name":"Environmental Sciences Europe","volume":null,"pages":null},"PeriodicalIF":5.9000,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://enveurope.springeropen.com/counter/pdf/10.1186/s12302-022-00603-5","citationCount":"2","resultStr":"{\"title\":\"Statistical analysis of avian reproduction studies\",\"authors\":\"John W. 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We present benefits and limitations of this BMD approach for older studies being re-evaluated and for new studies designed for with BMD analysis anticipated. Model averaging is recommended as preferable to model selection for BMD analysis. Even for a new study following the modified experimental design analyses, with BMD methodology will only be possible for a restricted set of response variables. The judicious use of historical control data, identification of outlier data points, increased use of distributions more consistent with the nature of the data collected as opposed to forcing normality-based methods, and trend-based hypothesis tests are shown to be effective for many studies, but limitations on their applicability are also recognized and explained. Updated statistical methodologies are illustrated with case studies conducted under existing regulatory guidelines that have been submitted for product registrations. Through the adoption of alternative avian reproduction study design elements combined with the suggested revised statistical methodologies the conduct, analyses, and utility of avian reproduction studies for avian risk assessments can be improved.</p></div>\",\"PeriodicalId\":54293,\"journal\":{\"name\":\"Environmental Sciences Europe\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2022-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://enveurope.springeropen.com/counter/pdf/10.1186/s12302-022-00603-5\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Sciences Europe\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s12302-022-00603-5\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Sciences Europe","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1186/s12302-022-00603-5","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Environmental Science","Score":null,"Total":0}
Statistical analysis of avian reproduction studies
Avian reproduction studies for regulatory risk assessment are undergoing review by regulatory authorities, often leading to requests for statistical re-analysis of older studies using newer methods, sometimes with older study data that do not support these newer methods. We propose detailed statistical protocols with updated statistical methodology for use with both new and older studies and recommend improvements in experimental study design to set up future studies for robust statistical analyses. There is increased regulatory and industry attention to the potential use of benchmark dose (BMD) methodology to derive the endpoint to be used in avian reproduction studies for regulatory risk assessment. We present benefits and limitations of this BMD approach for older studies being re-evaluated and for new studies designed for with BMD analysis anticipated. Model averaging is recommended as preferable to model selection for BMD analysis. Even for a new study following the modified experimental design analyses, with BMD methodology will only be possible for a restricted set of response variables. The judicious use of historical control data, identification of outlier data points, increased use of distributions more consistent with the nature of the data collected as opposed to forcing normality-based methods, and trend-based hypothesis tests are shown to be effective for many studies, but limitations on their applicability are also recognized and explained. Updated statistical methodologies are illustrated with case studies conducted under existing regulatory guidelines that have been submitted for product registrations. Through the adoption of alternative avian reproduction study design elements combined with the suggested revised statistical methodologies the conduct, analyses, and utility of avian reproduction studies for avian risk assessments can be improved.
期刊介绍:
ESEU is an international journal, focusing primarily on Europe, with a broad scope covering all aspects of environmental sciences, including the main topic regulation.
ESEU will discuss the entanglement between environmental sciences and regulation because, in recent years, there have been misunderstandings and even disagreement between stakeholders in these two areas. ESEU will help to improve the comprehension of issues between environmental sciences and regulation.
ESEU will be an outlet from the German-speaking (DACH) countries to Europe and an inlet from Europe to the DACH countries regarding environmental sciences and regulation.
Moreover, ESEU will facilitate the exchange of ideas and interaction between Europe and the DACH countries regarding environmental regulatory issues.
Although Europe is at the center of ESEU, the journal will not exclude the rest of the world, because regulatory issues pertaining to environmental sciences can be fully seen only from a global perspective.