Number of covariates - MRDS

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Camille Ollier

Oct 21, 2022, 9:51:36 AM10/21/22
to distance-sampling
Hello,

Is there a general rule about the maximum number of covariates that can be included in an mrds model?

I heard from a distance sampling workshop that it is best not to use many covariates. Do you know of an article on this subject?

Best regards,

Camille Ollier

Oct 21, 2022, 10:06:59 AM10/21/22
to Camille Ollier, distance-sampling
Camille

The issue of covariates differs between conventional distance sampling (of which I spoke during the introductory workshop) and distance sampling when g(0)<1 (which uses the mrds approach).

Because the mrds (or double observer) approach uses mark-recapture analysis (the "mr" in "mrds"), more extensive modelling of the "mr" portion of the double observer analysis is required.  This is because mark-recapture modelling does not possess the pooling robustness property, possessed by conventional distance sampling. In the absence of the pooling robustness property, sources of heterogeneity must be modelled to prevent bias.

This paragraph is from a paper by Borchers et al. (1998):

Using similar arguments to those of Patil et al. (1993), one can show that, when detection on the trackline is not certain, the p.d.f. of the observed data is not the same when mean detection functions, averaged over z, are used in place of detection functions that depend on z, even when the true forms of the mean detection functions are known. Inferences will in general be biased when sources of heterogeneity in detection probabilities are not modelled. This is a phenomenon that has long been recognized in MR studies. As a consequence, it is not in general possible to have pooling robust estimators (Burnham, Anderson, and Laake, 1980) in the presence of uncertain detection of animals on the trackline. (An estimator is pooling robust if it yields approximately unbiased estimates whether or not data are pooled over z.)
Borchers, D. L., Zucchini, W., & Fewster, R. (1998). Mark-recapture models for line transect surveys. Biometrics, 54, 1207–1220. https://doi.org/10.2307/2533651