{"title":"The Use of Effect Size in Veterinary Medicine: An Alternative Approach to p Value","authors":"P. Ambarcioglu","doi":"10.24880/MAEUVFD.823493","DOIUrl":null,"url":null,"abstract":"Effect size is a statistical index that measures the magnitude of the effect generated by the variable of interest in a study, in a sense, reflecting the practical or clinical value of the study in addition to the statistical results. In recent years, it has become preferable to report the effect size expressing practical significance in addition to the statistical significance expressed by the p-value in hypothesis tests in scientific research, and even it has been required by some scientific journals. By reporting the effect size, it is possible to use it in statistical power analysis, to compare the results of the studies, and to determine the amount of the effect in the study. In this study, by mentioning the concept of effect size, the main effect size indices used according to research types are introduced. In addition, the calculation methods of the effect size indices commonly used for continuous and categorical outcome variables were given and interpreted with scenarios from the field of veterinary medicine. In conclusion, in order to be able to interpret the results of a study in clinical or practical terms, to present the analyzed data in more detail than the p-value, and to ensure its use in power analysis, it was suggested that researchers report effect size in their studies. Etki büyüklüğünün veteriner hekimliği alanında kullanımı ÖZ Etki büyüklüğü, bir çalışmada ilgilenilen değişkenin meydana getirdiği etkinin büyüklüğünü ölçen, bir anlamda çalışmanın istatistiksel sonuçlarına ek olarak, pratik veya klinik anlamdaki değerini de yansıtan istatistiksel bir indekstir. Son yıllarda bilimsel araştırmalarda hipotez testlerinde p değeri ile ifade edilen istatistiksel anlamlılığa ek olarak pratik anlamlılığı ifade eden etki büyüklüğünün de raporlanması tercih edilir hale gelmiş, hatta bazı bilimsel dergiler tarafından zorunlu kılınmıştır. Etki büyüklüğünün raporlanması ile istatistiksel güç analizinde yararlanılması, çalışmaların sonuçlarının karşılaştırılması ve çalışmada belirlenen etkinin miktarının belirlenmesi mümkün olmaktadır. Bu çalışmada etki büyüklüğü kavramından bahsedilerek, araştırma türlerine göre kullanılan başlıca etki büyüklüğü indeksleri tanıtılmıştır. Ayrıca, sürekli ve kategorik sonuç değişkenler için yaygın olarak kullanılan etki büyüklüğü indekslerinin hesaplama yöntemleri verilerek, veteriner hekimliği alanından senaryolar ile örneklendirilmiş ve yorumlanmıştır. Sonuç olarak, klinik veya pratik anlamda çalışma sonuçlarını yorumlayabilmek, incelenen veriyi p değerinden daha ayrıntılı şekilde sunabilmek, güç analizlerinde kullanımını sağlamak amacıyla, araştırmacıların çalışmalarında etki büyüklüğü raporlaması önerilmiştir. 1Department of Biostatistic, Faculty of Veterinary Medicine, Mustafa Kemal University, Hatay/TURKEY MAE Vet Fak Derg, 6 (1): 2833, 2021 DOI: 10.24880/maeuvfd.823493 Bu makaleye atıfta bulunmak için/ To cite this article: Ambarcıoğlu P. The use of effect size in veterinary medicine. MAE Vet Fak Derg. 2021; 6 (1) :28-33. INTRODUCTION Statistical significance tests have a history dating back to the 1700s. It was first used by the Scottish physician John Arbuthnot in evaluating the birth rate in London according to the sex of the newborn babies, but its use was not widespread until the 1900s (1). The use of hypothesis tests has become widespread with the development of Karl Pearson’s Chi-Square Goodness of Fit Test in 1900, William S. Gossett’s Student t-Test in 1908, and Ronald Fisher’s Analysis of Variance (ANOVA) in 1918 (2,3,4). It became popular after Fisher published his first book in 1925, Statistical Methods for Research Workers, and then The Design of Experiments in 1935 (1,5,6). Although the decision-making process based on observation data in scientific research is actually a complex process, the fact that the deterministic algorithm of hypothesis testing approach has reduced this process to a dichotomous form of accepting and rejecting the hypothesis. For this reason, the hypothesis testing approach has spread rapidly as an easy-to-use process for researchers (7). However, over time, as researchers perceived this process only as a tool used to reach statistical significance, it has become difficult to reach scientific generalizations, and consequently, it received serious criticism (8,9,10). Criticisms of the hypothesis testing approach argue that the effect size should be used to express practical or clinical significance, in addition to the statistical significance expressed by hypothesis testing. Indeed, organizations such as the American Educational Research Association (AERA) and the American Review","PeriodicalId":32481,"journal":{"name":"Mehmet Akif Ersoy Universitesi Veteriner Fakultesi Dergisi","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mehmet Akif Ersoy Universitesi Veteriner Fakultesi Dergisi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24880/MAEUVFD.823493","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Effect size is a statistical index that measures the magnitude of the effect generated by the variable of interest in a study, in a sense, reflecting the practical or clinical value of the study in addition to the statistical results. In recent years, it has become preferable to report the effect size expressing practical significance in addition to the statistical significance expressed by the p-value in hypothesis tests in scientific research, and even it has been required by some scientific journals. By reporting the effect size, it is possible to use it in statistical power analysis, to compare the results of the studies, and to determine the amount of the effect in the study. In this study, by mentioning the concept of effect size, the main effect size indices used according to research types are introduced. In addition, the calculation methods of the effect size indices commonly used for continuous and categorical outcome variables were given and interpreted with scenarios from the field of veterinary medicine. In conclusion, in order to be able to interpret the results of a study in clinical or practical terms, to present the analyzed data in more detail than the p-value, and to ensure its use in power analysis, it was suggested that researchers report effect size in their studies. Etki büyüklüğünün veteriner hekimliği alanında kullanımı ÖZ Etki büyüklüğü, bir çalışmada ilgilenilen değişkenin meydana getirdiği etkinin büyüklüğünü ölçen, bir anlamda çalışmanın istatistiksel sonuçlarına ek olarak, pratik veya klinik anlamdaki değerini de yansıtan istatistiksel bir indekstir. Son yıllarda bilimsel araştırmalarda hipotez testlerinde p değeri ile ifade edilen istatistiksel anlamlılığa ek olarak pratik anlamlılığı ifade eden etki büyüklüğünün de raporlanması tercih edilir hale gelmiş, hatta bazı bilimsel dergiler tarafından zorunlu kılınmıştır. Etki büyüklüğünün raporlanması ile istatistiksel güç analizinde yararlanılması, çalışmaların sonuçlarının karşılaştırılması ve çalışmada belirlenen etkinin miktarının belirlenmesi mümkün olmaktadır. Bu çalışmada etki büyüklüğü kavramından bahsedilerek, araştırma türlerine göre kullanılan başlıca etki büyüklüğü indeksleri tanıtılmıştır. Ayrıca, sürekli ve kategorik sonuç değişkenler için yaygın olarak kullanılan etki büyüklüğü indekslerinin hesaplama yöntemleri verilerek, veteriner hekimliği alanından senaryolar ile örneklendirilmiş ve yorumlanmıştır. Sonuç olarak, klinik veya pratik anlamda çalışma sonuçlarını yorumlayabilmek, incelenen veriyi p değerinden daha ayrıntılı şekilde sunabilmek, güç analizlerinde kullanımını sağlamak amacıyla, araştırmacıların çalışmalarında etki büyüklüğü raporlaması önerilmiştir. 1Department of Biostatistic, Faculty of Veterinary Medicine, Mustafa Kemal University, Hatay/TURKEY MAE Vet Fak Derg, 6 (1): 2833, 2021 DOI: 10.24880/maeuvfd.823493 Bu makaleye atıfta bulunmak için/ To cite this article: Ambarcıoğlu P. The use of effect size in veterinary medicine. MAE Vet Fak Derg. 2021; 6 (1) :28-33. INTRODUCTION Statistical significance tests have a history dating back to the 1700s. It was first used by the Scottish physician John Arbuthnot in evaluating the birth rate in London according to the sex of the newborn babies, but its use was not widespread until the 1900s (1). The use of hypothesis tests has become widespread with the development of Karl Pearson’s Chi-Square Goodness of Fit Test in 1900, William S. Gossett’s Student t-Test in 1908, and Ronald Fisher’s Analysis of Variance (ANOVA) in 1918 (2,3,4). It became popular after Fisher published his first book in 1925, Statistical Methods for Research Workers, and then The Design of Experiments in 1935 (1,5,6). Although the decision-making process based on observation data in scientific research is actually a complex process, the fact that the deterministic algorithm of hypothesis testing approach has reduced this process to a dichotomous form of accepting and rejecting the hypothesis. For this reason, the hypothesis testing approach has spread rapidly as an easy-to-use process for researchers (7). However, over time, as researchers perceived this process only as a tool used to reach statistical significance, it has become difficult to reach scientific generalizations, and consequently, it received serious criticism (8,9,10). Criticisms of the hypothesis testing approach argue that the effect size should be used to express practical or clinical significance, in addition to the statistical significance expressed by hypothesis testing. Indeed, organizations such as the American Educational Research Association (AERA) and the American Review
效应大小是一个统计指标,衡量研究中感兴趣变量产生的效应的大小,从某种意义上说,除了统计结果外,还反映了研究的实际或临床价值。近年来,在科学研究中,除了用假设检验中的p值表示的统计显著性之外,报告表达实际显著性的效应大小变得更可取,甚至一些科学期刊也要求这样做。通过报告效应大小,可以将其用于统计功率分析,比较研究结果,并确定研究中的效应量。在本研究中,通过提及效应大小的概念,介绍了根据研究类型使用的主要效应大小指标。此外,给出了常用于连续和分类结果变量的效应大小指数的计算方法,并用兽医领域的情景进行了解释。总之,为了能够从临床或实践角度解释研究结果,比p值更详细地呈现分析数据,并确保其在功率分析中的使用,建议研究人员在研究中报告效应大小。在兽医学领域,Öz效应的使用是一种统计指标,用于衡量影响转化为工作的大小,包括工作、实际或临床意义的统计后果。在过去的几年里,科学研究倾向于报道影响的程度,表达实际意义,以及在假设检验中表达的统计意义,甚至是一些科学杂志。可以使用统计强度分析来报告影响大小,比较工作结果,并确定工作中定义的影响数量。在这项研究中,已经确定了用于研究类型的初始影响程度指数。此外,通过给出通常用于连续和分类变化的影响程度的计算方法,对兽医科学领域进行了抽样,并根据情景进行了解释。Sonuçolarak、klinik veya pratik anlamdaçalışma Sonuçlarınıyorumlayabilmek、incelenen veriyi p değerinden daha ayrıntılış。1穆斯塔法·凯末尔大学兽医学院生物统计学系,Hatay/TURKEY MAE Vet Fak Derg,6(1):28332021 DOI:10.24880/maeufd.823493本文:Ambarcıoğlu P.效应大小在兽医中的应用。MAE兽医假Derg2021年;6(1):28-33。引言统计学显著性测试的历史可以追溯到18世纪。苏格兰医生John Arbuthnot首次使用它根据新生儿的性别评估伦敦的出生率,但直到20世纪才广泛使用(1)。随着1900年Karl Pearson的卡方拟合良好性检验、1908年William s.Gossett的学生t检验和1918年Ronald Fisher的方差分析(ANOVA)的发展,假设检验的使用已经变得广泛(2,3,4)。1925年,费舍尔出版了他的第一本书《研究工作者的统计方法》,1935年出版了《实验设计》(1,5,6),之后这本书开始流行起来。尽管科学研究中基于观测数据的决策过程实际上是一个复杂的过程,但假设检验方法的确定性算法将这一过程简化为接受和拒绝假设的二分形式。因此,假设检验方法作为研究人员易于使用的过程迅速传播开来(7)。然而,随着时间的推移,由于研究人员只将这一过程视为一种用于达到统计显著性的工具,因此很难达到科学概括,因此,它受到了严重的批评(8,9,10)。对假设检验方法的批评认为,除了假设检验所表达的统计学意义外,效应大小还应用于表达实际或临床意义。事实上,美国教育研究协会(AERA)和《美国评论》等组织