I am trying to run 2x2 mixed ANOVA with unequal sample size using R. The data was collected from 30 individuals with two different conditions (i.e., 2 levels of within factor), and they were allocated by k-means clustering analysis (i.e., # of group 1 = 11, # of group 2 = 19). Here is a sample of my code and the output:
summary(aov(JH ~ Box+Group+Box:Group+Error(P/Box), data = d3))
Error: P
Df Sum Sq Mean Sq F value Pr(>F)
Group 1 0.027 0.02715 1.56 0.22
Box:Group 1 0.001 0.00078 0.04 0.83
Residuals 27 0.470 0.01741
Error: P:Box
Df Sum Sq Mean Sq F value Pr(>F)
Box 1 0.000000 1.00e-07 0.00 0.97
Group 1 0.000022 2.17e-05 0.24 0.63
Box:Group 1 0.000032 3.24e-05 0.35 0.56
Residuals 27 0.002488 9.21e-05
Unlike the output when I ran 2x2 mixed ANOVA with equal sample sizes using another dataset (the output attached below), I had another interaction effect under Error: P.
summary(aov(HipLoadingK ~ Box*Sex+Error(P/Box), data = TW))
Error: P
Df Sum Sq Mean Sq F value Pr(>F)
Sex 1 0.02578 0.025779 8.038 0.00841 **
Residuals 28 0.08980 0.003207
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Error: P:Box
Df Sum Sq Mean Sq F value Pr(>F)
Box 1 0.003454 0.003454 4.271 0.0481 *
Box:Sex 1 0.000066 0.000066 0.082 0.7765
Residuals 28 0.022645 0.000809
Is this result fine as long as I interpret appropriate results for each between/within main effects and interaction effect? Or should I edit my code to get the correct outputs? If so, please let me know what should be added or edited in my code.