Hello everyone,
in our study, we look at the effects of typical/enhanced body checking on eating pathology before and after the intervention,depending on the level of body concern (see below). Since the assumptions for a 3-way mixed ANOVA are not met, we'd like to conduct the robust alternative using the WRS package on R. There is a function called bwwtrim (function (J, K, L, data, tr=0.2, grp = c(1:p), alpha = 0.05, p=J * K *L) that seems to be what we need. However, I don't find any instruction on how to use it. In what format do the data need to be? How do I need to fill in the formula?
Here are the variables and factors we use:
Independent variables:
1. factor (between-subjects) = Body concern (high/low)
2. factor (within-subjects) = Condition (typical frequency / 3x increased frequency of Body Checking)
3. factor (within-subjects) = Time (pre / post intervention)
Dependent variable:
eg. Score on the "Drive for Thinness" questionnaire (Eating pathology)
For our 2-way mixed ANOVA (bwtrim function of the WRS2 package), I found a very helpful summary by the authors themselves (Robust Statistical Methods Using WRS2, Mair & Wilcox, https://rdrr.io/cran/WRS2/#vignettes). Is there something similar for the bwwtrim function?
Thank you a lot for your help!
All the best,
Hannah Bauer
You can use the f1.LD.f2 (between x within x within) function from the nparLD (non-parametric Long data) R package from Brunner and colleagues.
In my opinion this is a better alternative than the function from the WRS2 package because it does not trim the data.
See:
https://cran.r-project.org/web/packages/nparLD/nparLD.pdf
Rand Wilcox is at the university of Southern California Los Angeles. He wrote a series on these packages. These books are available in the z-library and Rand Wilcox is here on Researchgate so you can message him directly. Best wishes David Booth
see: https://stats.stackexchange.com/questions/591890/how-to-use-the-bwwtrim-function-of-the-wrs-package-robust-3-way-mixed-anova
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