 Analysis of Variance with Two FactorsWilliam H. Holmes () and
William C. Rinaman ()
Chapter 12 in Statistical Literacy for Clinical Practitioners, 2014, pp 303-339 from Springer Abstract: Abstract Previous chapters have presented statistical techniques for studying the relationship between a response variable and a single explanatory variable. The remaining chapters discuss techniques that investigate the relationship between a response variable and two or more explanatory variables, and that determine whether the impact of one explanatory variable varies across values of a second. In this chapter, two-way analysis of variance, also known as two-way ANOVA, is reviewed. This technique is appropriate when the response variable is quantitative, and is used to test null hypotheses about the main effects of two categorical explanatory variables, and the interaction effect between them. Three examples of two-way ANOVA are discussed: one in which both explanatory variables are independent groups, one in which both are repeated measures, and one in which one variable is independent groups and one is repeated measures. Keywords: Physical Activity; Body Mass Index; Independent Group; Average Body Mass Index; Chronic Headache (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-12550-3_12 Ordering information: This item can be ordered from DOI: 10.1007/978-3-319-12550-3_12 Access Statistics for this chapter More chapters in Springer Books from Springer |
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