The one-way ANOVA test explained

被引:30
作者
Chatzi, Anna [1 ]
Doody, Owen [1 ]
机构
[1] Univ Limerick, Limerick, Ireland
关键词
data analysis; quantitative research; research; study design; STATISTICS;
D O I
10.7748/nr.2023.e1885
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
Background Quantitative methods and statistical analysis are essential tools in nursing research, as they support researchers testing phenomena, illustrate their findings clearly and accurately, and provide explanation or generalisation of the phenomenon being investigated. The most popular inferential statistics test is the one-way analysis of variance (ANOVA), as it is the test designated for comparing the means of a study's target groups to identify if they are statistically different to the others. However, the nursing literature has identified that statistical tests are not being used correctly and findings are being reported incorrectly. Aim To present and explain the one-way ANOVA. Discussion The article presents the purpose of inferential statistics and explains one-way ANOVA. It uses relevant examples to examine the steps needed to successfully apply the one-way ANOVA. The authors also provide recommendations for other statistical tests and measurements in parallel to one-way ANOVA. Conclusion Nurses need to develop their understanding and knowledge of statistical methods, to engage in research and evidence-based practice. Implications for practice This article enhances the understanding and application of one-way ANOVAs by nursing students, novice researchers, nurses and those engaged in academic studies. Nurses, nursing students and nurse researchers need to familiarise themselves with statistical terminology and develop their understanding of statistical concepts, to support evidence-based, quality, safe care.
引用
收藏
页码:8 / 14
页数:7
相关论文
共 27 条
[21]   Application of Repeated-Measures Analysis of Variance and Hierarchical Linear Model in Nursing Research [J].
Shin, Juh Hyun .
NURSING RESEARCH, 2009, 58 (03) :211-217
[22]   Pervasive errors in hypothesis testing: Toward better statistical practice in nursing research [J].
Staggs, Vincent S. .
INTERNATIONAL JOURNAL OF NURSING STUDIES, 2019, 98 :87-93
[24]   Making sense of Cronbach's alpha [J].
Tavakol, Mohsen ;
Dennick, Reg .
INTERNATIONAL JOURNAL OF MEDICAL EDUCATION, 2011, 2 :53-55
[25]   Redressing the power and effect of significance. A new approach to an old problem: teaching statistics to nursing students [J].
Taylor, S ;
Muncer, S .
NURSE EDUCATION TODAY, 2000, 20 (05) :358-364
[26]   The Kruskal-Wallis test and stochastic homogeneity [J].
Vargha, A ;
Delaney, HD .
JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 1998, 23 (02) :170-192
[27]   Statistical Reporting in Nursing Research: Addressing a Common Error in Reporting ofpValues (p= .000) [J].
Wu, Yanni ;
Zhou, Chunlan ;
Wang, Run ;
Ye, Xiaoling ;
Yang, Lixiao ;
Li, Chaixiu ;
Hu, Mingyu ;
Cong, Weilian .
JOURNAL OF NURSING SCHOLARSHIP, 2020, 52 (06) :688-695