I read a short thread on this topic from last June on stackoverflow.com. Both Bryan Hanson and Ben Bolker suggested looking for such functions using the sos package. I did this; the nonpartest function in npmv does not look to me like it does what I need. Since that thread did not reach a definitive conclusion (no response by the original poster) I would like to continue my search here.
Context: water quality constituent concentrations measured multiple times from each of several monitoring wells with the latter in two groups: up- and down-gradient from a site of potential ground water contamination. To compare variation within individual monitoring wells with variation between the wells I'd use the Kruskal-Wallis test. That would also be appropriate to compare variation within each group (up-gradient and down-gradient) with variation between the two groups. My understanding of multiple analysis of variance is this would allow multiple sources of variability (intra-well and between wells) as explanatory variables for the response variable of a specified chemical constituent. The help page for nonpartest() tells me that it analyzes one-way multivariate data. Perhaps my understanding of this is poor, but the help page tells me that nonpartest() formula has a single explanatory variable and multiple response variables. In the context above, I have a single response variable (a chemical constituent concentration) and multiple explanatory variables (at least date, well, and location). Please confirm that my understanding of nonpartest() is correct and suggest an appropriate R protocol to analyze concentration variability within monitoring wells and between two well locations (up- and down-gradient). TIA, Rich ______________________________________________ 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.
