I'm still learning and trying out how Rmark modeling works. I work with a simplified subset of my dataset. I use data of one colony since 2002 and of a second colony since 2013. Therefore I use "remove.unused = T" during data processing to remove years that don't have data for the second colony. That's correct, isn't it?
I'm actually trying out how p is best defined and explore how models behave. Next to time and colony, I added effort (as factor) and Effort (as numeric) to the design data. Effort is the numer of days on which we captured the bats.
However, all models that contain the variable time are the same.
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model npar AICc DeltaAICc weight Deviance
8 Phi(~1)p(~-1 + time:colony) 28 2607.317 0.000000 2.451896e-01 1345.137
9 Phi(~1)p(~-1 + time:colony + effort) 28 2607.317 0.000000 2.451896e-01 1345.137
10 Phi(~1)p(~-1 + time:colony + Effort) 28 2607.317 0.000000 2.451896e-01 1345.137
11 Phi(~1)p(~time * colony) 28 2607.317 0.000000 2.451896e-01 1345.137
7 Phi(~1)p(~time) 20 2612.407 5.089894 1.924180e-02 1366.909
6 Phi(~1)p(~Effort * colony) 5 2656.886 49.568486 4.225148e-12 1442.057
3 Phi(~1)p(~-1 + effort:colony) 12 2658.420 51.102640 1.962026e-12 1429.377
5 Phi(~1)p(~effort * colony) 12 2658.420 51.102640 1.962026e-12 1429.377
4 Phi(~1)p(~-1 + Effort:colony) 3 2664.033 56.715769 1.185302e-13 1453.235
1 Phi(~1)p(~effort) 7 2670.853 63.535978 3.915973e-15 1451.981
2 Phi(~1)p(~Effort) 3 2677.362 70.044669 0.000000e+00 1466.564
If I look at the model outputs, model 8 looks fine. However, model 9, 10 have 0 for all standart errors for p and model 11 has 0 for all standart errors for p in the second colony (2013-2021). I assume, all time models besides model 8 didn't converge. I tried to test this like it is described in the Rmark workshop notes using
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with(results$model.table, tapply(Neg2LnL, list(Phi,p),unique))
but the model table doesn't contain a column with Neg2LnL.
Whats wrong?
Tanks,
best
Bianca