This looks more like a statistics than an R issue. Try posting on stats.stackexchange.com, a statistics list, instead.
ALternatively, talk to your local statistician (if there is one). -- Bert On Tue, Sep 18, 2012 at 3:02 PM, McPhie, Romney <romney.mcp...@dfo-mpo.gc.ca> wrote: > Hello, > > I have some satellite tag time-at-depth (TAD) frequency data that I > would like some help with. > > The data was transmitted via satellite as percent time spent in each of > 7 depth bins (0m, 0-1m, 1-10m, 10-50m etc.), binned over 6-hour > intervals. I categorized each row of data corresponding to a date and > time into summer vs. winter, and day vs. night, and then summed and > averaged the given % for each depth bin. My data looks like this (for > one individual, HG03): > > HG03.dat > Season Time Depth Sum Avrg > 1 summ day 0 17.2 0.1702970 > 2 summ day 1 23.9 0.2366337 > 3 summ day 10 868.5 8.5990099 > 4 summ day 50 2698.2 26.7148515 > 5 summ day 100 419.7 4.1554455 > 6 summ day 200 266.1 2.6346535 > 7 summ day 300 1668.6 16.5207921 > 8 summ day 500 4138.2 40.9722772 > 9 summ night 0 283.6 5.7877551 > 10 summ night 1 229.1 4.6755102 > 11 summ night 10 479.3 9.7816327 > 12 summ night 50 761.9 15.5489796 > 13 summ night 100 235.8 4.8122449 > 14 summ night 200 40.9 0.8346939 > 15 summ night 300 763.1 15.5734694 > 16 summ night 500 2106.1 42.9816327 > 17 wint day 0 0.0 0.0000000 > 18 wint day 1 0.0 0.0000000 > 19 wint day 10 0.0 0.0000000 > 20 wint day 50 0.0 0.0000000 > 21 wint day 100 7.9 1.1285714 > 22 wint day 200 92.1 13.1571429 > 23 wint day 300 0.0 0.0000000 > 24 wint day 500 600.0 85.7142857 > 25 wint night 0 43.9 1.7560000 > 26 wint night 1 0.3 0.0120000 > 27 wint night 10 0.3 0.0120000 > 28 wint night 50 0.8 0.0320000 > 29 wint night 100 10.5 0.4200000 > 30 wint night 200 51.6 2.0640000 > 31 wint night 300 411.4 16.4560000 > 32 wint night 500 1981.2 79.2480000 > > I wanted to test whether significant differences existed between depth > in summer vs. winter, and day vs. night, controlling first for season > and then for time of day. I carried out a Cochran-Mantel-Haenszel test, > using Average Frequency (Avrg) as the dependent variable (2x2x8 > contingency table). > >> ct<-xtabs(Avrg~Time+Depth+Season,data=HG03.dat) >> mantelhaen.test(ct) > > Cochran-Mantel-Haenszel test > > data: ct > Cochran-Mantel-Haenszel M^2 = 28.4548, df = 7, p-value = 0.0001818 > >> ct<-xtabs(Avrg~Season+Depth+Time,data=HG03.dat) >> mantelhaen.test(ct) > > Cochran-Mantel-Haenszel test > > data: ct > Cochran-Mantel-Haenszel M^2 = 111.5986, df = 7, p-value < 2.2e-16 > > However, I'm not sure if these results are valid, since my raw data is > already in frequencies, not in counts. When I used Sum as the dependent > variable, I obtained different results. > > I am at a loss on how to proceed. If anyone has any ideas, they would > be greatly appreciated. > > Thanks! > Romney > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ 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.
