{"title":"Reporting and Interpreting Multivariate Analysis of Variance (MANOVA): Adopting the Best Practices in Educational Research","authors":"Simon Ntumi","doi":"10.14505/jres.v12.14.05","DOIUrl":null,"url":null,"abstract":"There is seemingly anonymity and observation among consumers of educational research that multivariate analysis of variance (MANOVA) is one of the most predominant and commonly used statistical models for the analysis of data in the discipline of education. Despite the large use of MANOVA in research studies, most research practitioners within the educational research trail still face difficulties in reporting and meaningfully interpreting MANOVA results. In analysis, multivariate analysis of variance tests for two or more independent variables and two or more dependent variables. In practice, the one-way multivariate analysis of variance is used to determine whether there are any differences between independent groups on more than one continuous dependent variable. This paper provides a data driven example of reporting and interpreting presentation of multivariate analysis of variance for consumers of research by capitalizing on how it can be reported and interpreted using the APA format. In the paper, the researcher used an example data-driven set throughout the write up to illustrate how MANOVA is reported and interpreted in educational studies. The paper emphasized that if researchers do not run the statistical tests on assumptions of using MANOVA correctly, the accrued results that will be might not be valid. These could therefore have structural effects on the conclusions and implications that will be drawn from the analysis. The paper concludes with remarks that throws more lights and emphasis on the relevant and consequent implications of using MANOVA in educational studies.","PeriodicalId":350338,"journal":{"name":"Journal of Research in Educational Sciences","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Research in Educational Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14505/jres.v12.14.05","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
There is seemingly anonymity and observation among consumers of educational research that multivariate analysis of variance (MANOVA) is one of the most predominant and commonly used statistical models for the analysis of data in the discipline of education. Despite the large use of MANOVA in research studies, most research practitioners within the educational research trail still face difficulties in reporting and meaningfully interpreting MANOVA results. In analysis, multivariate analysis of variance tests for two or more independent variables and two or more dependent variables. In practice, the one-way multivariate analysis of variance is used to determine whether there are any differences between independent groups on more than one continuous dependent variable. This paper provides a data driven example of reporting and interpreting presentation of multivariate analysis of variance for consumers of research by capitalizing on how it can be reported and interpreted using the APA format. In the paper, the researcher used an example data-driven set throughout the write up to illustrate how MANOVA is reported and interpreted in educational studies. The paper emphasized that if researchers do not run the statistical tests on assumptions of using MANOVA correctly, the accrued results that will be might not be valid. These could therefore have structural effects on the conclusions and implications that will be drawn from the analysis. The paper concludes with remarks that throws more lights and emphasis on the relevant and consequent implications of using MANOVA in educational studies.
多变量方差分析(multivariate analysis of variance, MANOVA)是教育学科中最主要、最常用的数据分析统计模型之一,这一点在教育研究的消费者中似乎不为人知。尽管在研究中大量使用了方差分析,但大多数教育研究领域的研究从业者在报告和有意义地解释方差分析结果方面仍然面临困难。在分析中,对两个或多个自变量和两个或多个因变量进行方差检验的多变量分析。在实践中,单向多变量方差分析用于确定独立组之间在多个连续因变量上是否存在差异。本文提供了一个数据驱动的例子,通过利用如何使用APA格式进行报告和解释,为研究消费者提供了多变量方差分析的报告和解释。在论文中,研究人员在整个写作中使用了一个示例数据驱动集来说明MANOVA在教育研究中是如何报告和解释的。这篇论文强调,如果研究人员没有正确地对使用方差分析的假设进行统计检验,那么累积的结果可能是无效的。因此,这些可能对将从分析中得出的结论和所涉问题产生结构性影响。本文的结论是对在教育研究中使用方差分析的相关和后续含义进行了更多的阐述和强调。