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I'm pulling my hair out trying to figure out what I'm going wrong. I ran a model with body length (ind cov) on survival using RDHuggins. I get the same exact results (deviance) in RMark as in Mark. The only difference is, when I use covariate.predictions, the output $estimates does not contain different values for survival- only the single real parameter estimate. I can plot them no problem from within Mark (using independently built model, I have not tried exporting).

For example, when I run this:

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S_by_BL=covariate.predictions(model,data=BL.values,indices=1)

I get this:

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vcv.index model.index par.index  covdata  estimate        se       lcl       ucl fixed
1          1           1         1 13.30000 0.8503256 0.1094139 0.5130401 0.9683894     
2          2           1         1 14.13767 0.8503256 0.1094139 0.5130401 0.9683894     
3          3           1         1 14.97533 0.8503256 0.1094139 0.5130401 0.9683894     
4          4           1         1 15.81300 0.8503256 0.1094139 0.5130401 0.9683894     
5          5           1         1 16.65067 0.8503256 0.1094139 0.5130401 0.9683894     
6          6           1         1 17.48833 0.8503256 0.1094139 0.5130401 0.9683894     
7          7           1         1 18.32600 0.8503256 0.1094139 0.5130401 0.9683894     
8          8           1         1 19.16367 0.8503256 0.1094139 0.5130401 0.9683894   

when I was expecting to fine that $estimates$estimate would be a product of the slope equation from the model. Any tips? Thanks in advance.

Nate

What was the structure of BL.values and what was the formula? The names of the variables in the dataframe (BL.values) have to match the names of the variables used in the formula.

--jeff

You know I knew I had to make sure the names were the same and I was certain that they were. Except they weren't actually the same. Thanks for pointing out that glaring oversight!! *crawls back under rock