I'm trying to create a cohort variable for a square PIMS. I have added the year first seen in the input ch (as Year) for each animal and am using the following;
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capt.pr <- process.data(data,begin.time = 2014, model = "POPAN",
groups = c("sex", "Year"))
I'm not sure if I've done this correctly because despite being the 'top model' (with lowest AICc) the standard errors are absolutely huge. I would guess that the data isn't sufficient for year covariets however the AIC is far 'lower' and any dot or otherwise models.
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model npar AICc DeltaAICc weight Deviance
52 Phi(~Year)p(~time)pent(~Year)N(~1) 19 505.6249 0.000000 5.761502e-01 185.3868
Output summary for POPAN model
Name : Phi(~Year)p(~time)pent(~Year)N(~1)
Npar : 19 (unadjusted=10)
-2lnL: 463.8811
AICc : 505.6249 (unadjusted=484.91881)
Beta
estimate se lcl ucl
Phi:(Intercept) 1.0088768 1.965698e-01 6.236000e-01 1.394154e+00
Phi:Year2015 -0.0482977 4.064769e-01 -8.449924e-01 7.483971e-01
Phi:Year2016 -1.0978776 5.134463e-01 -2.104233e+00 -9.152280e-02
Phi:Year2017 -0.5171342 5.622330e-01 -1.619111e+00 5.848425e-01
Phi:Year2018 -41.8050200 4.801592e+04 -9.415301e+04 9.406940e+04
Phi:Year2019 63.8141650 7.270434e+04 -1.424367e+05 1.425643e+05
p:(Intercept) 2.9985974 8.850260e-01 1.263946e+00 4.733249e+00
p:time2015 -0.5741594 1.010561e+00 -2.554858e+00 1.406540e+00
p:time2016 0.4431593 1.335746e+00 -2.174902e+00 3.061221e+00
p:time2017 -1.3503223 1.021704e+00 -3.352861e+00 6.522169e-01
p:time2018 -1.2904555 1.024393e+00 -3.298266e+00 7.173554e-01
p:time2019 12.7330420 2.247753e+03 -4.392863e+03 4.418329e+03
pent:(Intercept) -5.5745870 1.761071e+00 -9.026287e+00 -2.122887e+00
pent:Year2015 78.2985190 8.895199e+04 -1.742676e+05 1.744242e+05
pent:Year2016 72.5578700 8.251250e+04 -1.616519e+05 1.617970e+05
pent:Year2017 42.7271000 4.905025e+04 -9.609577e+04 9.618123e+04
pent:Year2018 57.8648340 6.603079e+04 -1.293625e+05 1.294782e+05
pent:Year2019 55.8441220 6.376409e+04 -1.249218e+05 1.250335e+05
N:(Intercept) -19.9187590 3.402224e+03 -6.688277e+03 6.648440e+03
I have two further questions about including the cohort covariate which I'm a little confused about (and have read the workshop notes) and I'm wondering if this could be the problem partly
-how can I include first capture event in the likelihood?
- There is a bias towards when surveying started (2014) so would it be best to set '2014' to NA in the input, that way the model will just look at animals definitely seen in 2015+?
Looking forward to any suggestions!
Many thanks in advance