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Analysis of Variance with Two Factors

In: Statistical Literacy for Clinical Practitioners

Author

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  • William H. Holmes

    (Le Moyne College)

  • William C. Rinaman

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.

Suggested Citation

  • William H. Holmes & William C. Rinaman, 2014. "Analysis of Variance with Two Factors," Springer Books, in: Statistical Literacy for Clinical Practitioners, edition 127, chapter 12, pages 303-339, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-12550-3_12
    DOI: 10.1007/978-3-319-12550-3_12
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