The anova2
operator tests for a significant difference in the mean between any of the groups in the input data.
Input projection | . |
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y-axis |
measurement value |
colors |
represents the groups to compare |
Input parameters | . |
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Grouping Variable 1 |
Treat the ANOVA grouping variable 1 as categorical (dft) or numerical. |
Grouping Variable 2 |
Treat the ANOVA grouping variable 2 as categorical (dft) or numerical. |
Include Interaction |
Fit ANOVA model using a factor1:factor2 interaction term (dft = "No"). |
Output relations | . |
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pFactor1 |
p-value for the probability that all group means for Factor1 are equal (groupingType = categorical) or the slope of the straight line fit is equal to zero (groupingType = continuous), accounting for Factor2. Hence, a low value indicates a significant effect for Factor1. |
pFactor2 |
p-value for the probability that all group means for Factor2 are equal (groupingType = categorical) or the slope of the straight line fit is equal to zero (groupingType = continuous), accounting for Factor1. Hence, a low value indicates a significant effect for Factor2. |
pFactor3 |
p-value for the interaction between Factor1 and Factor2 (if required). A low value for pFactor3 indicates an effect of Factor2 that is different in the groups of Factor1 (or vice versa). |
logpFactor1-3 |
the significance of pFactors 1-3, respectively, as -10 log(pFactor). |
2-way ANOVA is used for data with two grouping factors, but with more than 2 groups. It test for a significant difference in the mean between any of the groups. As such, it is a generalization of the two sample t-test that works for two groups only. The operator is based on the anova R function.
The grouping factors must be added as data colors. The grouping can be by categorical and/or continuous variables. In the latter case a straight line regression is performed. There is an option to add an interaction term to the ANOVA model.