Dear all, I am conducting a full factorial analysis. I have one factor consisting in algorithms, which I consider my treatments, and another factor made of the problems I want to solve. For each problem I obtain a response variable which is stochastic. I replicate the measure of this response value 10 times.
When I apply ANOVA the assumptions do not hold, hence I must rely on non parametric tests. By transforming the response data in ranks, the Friedman test tells me that there is statistical significance in the difference of the sum of ranks of at least one of the treatments. I would like now to produce a plot for the multiple comparisons similar to the Least Significant Difference or the Tukey's Honest Significant Difference used in ANOVA. Since I am in the non parametric case I can not use these methods. Instead, I compare graphically individual treatments by plotting the sum of ranks of each treatment togehter with the 95% confidence interval. To compute the interval I use the Friedman test as suggested by Conover in "Practical Nonparametric statistics". I obtain something like this: Treat. A |-+-| Treat. B |-+-| Treat. C |-+-| Treat. D |-+-| The intervals have all the same spread because the number of replications was the same for all experimental units. I would like to know if someone in the list had a similar experience and if what I am doing is correct. In alternative also a reference to another list which could better fit my request is welcome. Thank you for the help, Marco -- Marco Chiarandini, Fachgebiet Intellektik, Fachbereich Informatik, Technische Universität Darmstadt, Hochschulstraße 10, D-64289 Darmstadt - Germany, Office: S2/02 Raum E317 Tel: +49 (0)6151 16-6802 Fax: +49 (0)6151 16-5326 email: [EMAIL PROTECTED] web page: http://www.intellektik.informatik.tu-darmstadt.de/~machud ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
