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
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