A reviewer suggested there are "more advanced and robust methods" to compare groups in my study that involves three groups comparison - two with Augmented Reality tools and one with a conventional marketing tool, same brand and same product type though.
The reviewer said "ANOVA is a useful and robust analysis tool if we compare directly measurable items. Unfortunately, this is not the case for this manuscript. Therefore, the findings of this comparison are questionable."
Could you provide more info on the DV/IV types (nominal/ordinal/continuous)? Personally I don't think ANOVA is less advanced than other tests -- it's more of a matter of what statistical test would be most suitable for your case. So certain tests could indeed be more robust than ANOVA in certain cases. You might already know this that ANOVA have several general assumptions. If you data does not meet these assumptions, non-parametric tests could be the alternatives. Based on this question's descriptions, it seems that it is an experiment with three conditions, which is usually vulnerable to non-normal data distributions if the sample size is small. Not sure what the reviewer meant by saying that your study did not have "directly measurable items," though.
Dear Ye Chen,
I suggest you see links on the topic.
https://ir.ua.edu/bitstream/handle/123456789/2136/file_1.pdf?sequence=1&isAllowed=y
https://eprints.lancs.ac.uk/id/document/60410
https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/425564/1/Dissertation_No26733_LukasPaulFesenfeld.pdf
https://scholarworks.wm.edu/cgi/viewcontent.cgi?article=7164&context=etd
https://manualzz.com/doc/9910448/a.r.ciupuliga_phd_thesis.
Best regards
Ye Chen Thanks for the clarification. Researchers have been using ANOVA on psychological and behavioral factors all the time, and so this should not be a problem. Please do investigate your data distributions, though. My collaborator used Welch's ANOVA for one of our studies where the DV data had unequal variances across three groups (i.e. when the homogeneity of variances assumption is violated). And there are other parametric tests for different use cases. Good luck!
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