

I have data on the proportion of clutches experiencing different fates
(e.g., 4 different sources of mortality) for 5 months . I need to test 1)
if the overall proportion of these different fates is different over the
entire study and 2) to see if there are monthly differences within (and
among) fate types. Thus, I am pretty sure this is an RM analysis -( I
measure the same quadrats each month).

I am fine running the analysis in R - with the code below, however, there
is no output for the among group variation...this is an important component
- any ideas on how to solve this problem?

I have included code and sample data below.

Many thanks in advance for help and suggestions.

J

 both.aov <- aov(ProportioninTreatment ~ factor(Treatment)*factor(Month) +
Error(factor(Quadrat)), RM)

Error: factor(id)
          Df  Sum Sq Mean Sq F value Pr(>F)
Residuals  3 0.51619 0.17206               #####why only partial output
here? #######

Error: Within
                   Df Sum Sq Mean Sq F value   Pr(>F)
factor(Fate1)       3 1.2453  0.4151  3.5899 0.017907 *
time                1 0.9324  0.9324  8.0637 0.005929 **
factor(Fate1):time  3 0.9978  0.3326  2.8763 0.042272 *
Residuals          69 7.9783  0.1156




Fate1 Proportion in Fate      ASIN  Month Quadrat
1     0.117647059 0.350105778 1     1
1     0     0     2     1
1     0.111111111 0.339836909 3     1
1     0     0     4     1
1     0     0     5     1
1     0     0     1     2
1     0     0     2     2
1     0.2   0.463647609 3     2
1     0.25  0.523598776 4     2
1     0.111111111 0.339836909 5     2
1     0     0     1     3
1     0     0     2     3
1     0     0     3     3
1     0.384615385 0.668964075 4     3
1     0     0     5     3
1     0     0     1     4
1     0     0     2     4
1     0     0     3     4
1     0.166666667 0.420534336 4     4
1     0     0     5     4
2     0.352941176 0.636132062 1     1
2     0.2   0.463647609 2     1
2     0.333333333 0.615479708 3     1
2     1     1.570796327 4     1
2     0     0     5     1
2     0.5   0.785398163 1     2
2     0     0     2     2
2     0.6   0.886077124 3     2
2     0.416666667 0.701674124 4     2
2     0.222222222 0.490882678 5     2
2     0     0     1     3
2     0.2   0.463647609 2     3
2     0     0     3     3
2     0.461538462 0.746898594 4     3
2     0     0     5     3
2     0     0     1     4
2     0     0     2     4
2     0.307692308 0.588002604 3     4
2     0.666666667 0.955316618 4     4
2     0     0     5     4
3     0     0     1     1
3     0     0     2     1
3     0.444444444 0.729727656 3     1
3     0     0     4     1
3     1     1.570796327 5     1
3     0.5   0.785398163 1     2
3     0     0     2     2
3     0     0     3     2
3     0.25  0.523598776 4     2
3     0.555555556 0.841068671 5     2
3     0     0     1     3
3     0     0     2     3
3     0     0     3     3
3     0.153846154 0.403057075 4     3
3     0.666666667 0.955316618 5     3
3     0     0     1     4
3     0     0     2     4
3     0     0     3     4
3     0     0     4     4
3     0.875 1.209429203 5     4
4     0.294117647 0.573203309 1     1
4     0.2   0.463647609 2     1
4     0     0     3     1
4     0     0     4     1
4     0     0     5     1
4     0     0     1     2
4     0     0     2     2
4     0     0     3     2
4     0.083333333 0.292842771 4     2
4     0.111111111 0.339836909 5     2
4     0     0     1     3
4     0     0     2     3
4     0     0     3     3
4     0     0     4     3
4     0.166666667 0.420534336 5     3
4     0     0     1     4
4     0     0     2     4
4     0.461538462 0.746898594 3     4
4     0     0     4     4
4     0.125 0.361367124 5     4
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