Unreliable estimates using 'derived' function
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Julien Piquet
Jul 27, 2020, 10:15:46 AM7/27/20
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Hi all,
I also published this topic on the PhiDot secr forum, but this group seems somehow more active...so sorry for the duplication.
Just to give a
proper background I will briefly explain what I am working on. I am
running currently analysing the data from a project that aims to
estimate lizard density on several sites, over a 5-month period. I have
14 sites (grouped in 3 main study areas), which I have visited twice per
month (5 sessions, 2 occasions). Half of these sites correspond to
capture locations within the area of an invasive predator, the other
half are control sites. Within the invaded sites, I have an extremely
low number of lizard captures. Therefore, to ensure model convergence I
ran separate models for each area, indicating that each site was a
separate session. To reduce computational burden, and work with 'closed'
populations, I further subdivided data in sessions, so that I finally
ran 3x5 models (for each study area and session combination). I ran all
models maximizing conditional likelihood (CL=T) to save some time, and
finally retrieved site-specific density using 'derived' function, and that's where my problem begins.
When I look at the estimates from derived function, I get some extremely odd results. Density looks like a really huge number (something like 9.402571e+15), whereas the esa is extremely small (3.349110e-08). At first glance, I thought this could mean that results are on the link scale and needed to be back-transformed. After that I started wondering if there could be any chance that the derived function changed the units (lizard/km^2, for instance). Another alternative (likely the most plausible) is that my model is wrong. After reading some papers I noticed secr models require a certain amount of recaptures to attain reliable results. I have 40-50 recaptures in the overall study, but after breaking up my dataset I am clearly below the safe minimum for secr models (10 recaptures per model). In spite of that, my CVD looks really good, with an average value of 9.02 for all models. Furthermore, when I run the models mximizing the full likelihood (CL=F) density estimates look much more decent (around 20 lizard/ha), although density in invaded sites is below zero, which is really weird. Right now I am struggling to understand whether the model is ok and I just missed something, or if should just migrate to non-spatial open-population models in openCR. Any feedback would be really helpful.
Thanks in advance!
When I look at the estimates from derived function, I get some extremely odd results. Density looks like a really huge number (something like 9.402571e+15), whereas the esa is extremely small (3.349110e-08). At first glance, I thought this could mean that results are on the link scale and needed to be back-transformed. After that I started wondering if there could be any chance that the derived function changed the units (lizard/km^2, for instance). Another alternative (likely the most plausible) is that my model is wrong. After reading some papers I noticed secr models require a certain amount of recaptures to attain reliable results. I have 40-50 recaptures in the overall study, but after breaking up my dataset I am clearly below the safe minimum for secr models (10 recaptures per model). In spite of that, my CVD looks really good, with an average value of 9.02 for all models. Furthermore, when I run the models mximizing the full likelihood (CL=F) density estimates look much more decent (around 20 lizard/ha), although density in invaded sites is below zero, which is really weird. Right now I am struggling to understand whether the model is ok and I just missed something, or if should just migrate to non-spatial open-population models in openCR. Any feedback would be really helpful.
Thanks in advance!
Murray Efford
Jul 28, 2020, 4:57:10 PM7/28/20
to secr
Please see phidot http://www.phidot.org/forum/viewtopic.php?f=36&t=4049&p=13403#p13403
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