> Here are the boxplots if that helps: > http://www.ps.masny.dk/guests/misc/A1.png > http://www.ps.masny.dk/guests/misc/A2.png > http://www.ps.masny.dk/guests/misc/C1.png > http://www.ps.masny.dk/guests/misc/C2.png
Here is how I would do it: It looks like your distributions can be characterized by just a single parameter. Then your question is: Is the change in the parameter value from A1 to A2 larger than that from C1 to C2? (Larger meaning what?: Difference? Ratio?) So I suggest - you estimate your four parameters - compute your two differences or ratios - compute the difference of those - and repeat all this for many resamples (bootstrapping) Then you get a bootstrap distribution of the value that you hope is significantly non-zero. >From that distribution you can read your p-value. (Preferably based on a BCa confidence interval) library(boot) Does that make sense? Lutz ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html