Hello I run a factorial analysis on 20 variables describing the behaviour of insects on 9 different resistant plants. I then biologically interpreted each of the 5 factors obtained, with respect to the variables with the highest loading value for each factor. And I run a GLM on each factor with plant as independent variable. Eventually, I inferred the resistance mechanism by comparing (through post-hoc Dunnett's test) the factor score between each resistant plant and a susceptible standard. This analysis gave me good results. However, I am worried that the factors I obtained may vary with the variability of the variables. For instance, if most of the plants exhibit the same type of resistance, resulting in a skewness of my dataset, do the factors reflect all the resistance mechanisms, even the ones in minority? Additionally, I would appreciate your opinion on conducting GLM on factors.
thank you very much in advance. Julien. -- View this message in context: http://n4.nabble.com/factorial-analysis-influenced-by-data-skewness-tp991087p991087.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
