I was wondering whether anyone had any suggestions as to what statistic to use (I use R Studio).
I have some muscle cell circumference measurements (response) and I have two explanatory variable columns (Control/Diet) and exercise (Yes/ No) (categorical) and I need the option to run an interaction between these explanatory variables (as I had 4 groups) as well as separately. A Bartlett's test states that its non-parametric data so does anyone have any suggestions as to what statistic/model I could use? I have looked into GLM's but as far as I can see, they don't work with interactions/ non-binomial data.
Thanks in advance for any recommendations.
There are (aligned) rank tests available. Th emost accessible is the ARTool:
See:
http://depts.washington.edu/acelab/proj/art/index.html
There is also the f1_LD_F1 test which is part of the R package nparLD or the f1_LD_f1SAS macro. See attachments. Shah & Madden explain and illustrate the method…
- paper_brunner_nparLD.pdf583.51 KB
- F1_LD_F1.sas34.41 KB
- luepsen_koeln.pdf182.99 KB
- shah&madden2004.pdf234.40 KB
- shahbrunner_electronic_app.pdf
I'm sorry you seem to have some misconceptions. There is nothing called nonparemetric data only nonparametric tests. You likely have a 2x2 factorial design which can most easily be dealt with as a regression: Resp=a + b*CD +f*EX + g*CD*EX +eps as the model. the g*CD*EX is the interaction term. See attachment chapter 1-6. Your model is covered in Chapt 6 Graph your data as in the interaction plots these are very important. Go to p. 126 where they discuss a model like yours but it has 1 more explanatory variable. See this example. Goto p.11 of the 2nd attachment, here is your model this example is in SAS in R put your model in the lm function. Go to p19 here is your example run this in R so you know it works you will get the same answer. Be sure you do. Now run your data in R This book will help you [ sgpwe.izt.uam.mx › files › users › uami › gma › R_for_dummies ] Now you should be OK. Best of luck. D. Booth
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