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.McPhie at 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]]
>
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--
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