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3 Way Factorial Anova. Factorial ANOVA or three-way between-subjects ANOVA. Or to use the more technically correct terminology we would say that there are two main effects of drug and therapy. A 3-way between groups ANOVA was used to examine the main effects and interactions of Food Offered Species and Age as they relate to the number of feeding strikes made. The p -value of 00158 indicates that the interaction between g1 and g2 is significant.
It is also called a three-factor ANOVA with ANOVA standing. As such it extends the two-way ANOVA which is used to determine if such an interaction exists between just two independent variables ie rather than three independent variables. The first three entries of p are the p -values for the main effects. In short its telling us that the factorial ANOVA for our 3 times 2 design found a significant effect of drug F_214 2615 p 001 as well as a significant effect of therapy F_114 708 p 02. If you are not familiar with three-way interactions in ANOVA please see our general FAQ on understanding three-way interactions in ANOVA. As you may recall a Factorial ANOVA attempts to compare the influence of at least two independent variables with at least two levels each eg 1.
The first three entries of p are the p -values for the main effects.
Although generally robust to assumption violations factorial ANOVA results are susceptible to bias especially when group sizes are disparate with unequal variances. The third design shows an example of a design with 2 IVs time of day and caffeine each with two levels. As you may recall a Factorial ANOVA attempts to compare the influence of at least two independent variables with at least two levels each eg 1. When the dialog box in Figure 1 appears enter A3D38 in the Input Range unclick Column headings included with data select Std by Columns as the Input Format select ANOVA as the Analysis Type and click on the OK button. At the moment it probably seems a bit redundant to refer to these as main effects. The three-way ANOVA is used to determine if there is an interaction effect between three independent variables on a continuous dependent variable ie if a three-way interaction exists.