[R-sig-ME] Plotting partial residuals from a glmmADMB model

[Ben Bolker]

You'll have to find a way to make "partial predictions". I don't think
there's anything built in for this.  *Very* briefly, considering
only fixed effects, if you retrieve the X matrix
(getME(fitted_model,"X")) and the fixed-effect parameters
(fixef(fitted_model)),
you can drop any columns/parameters you want and do exp(X %*% beta)
with the remaining columns/parameters to get a prediction
that includes some but not all of the predictors. Subtracting the
observed value should get you the partial residuals ...


On Tue, Dec 12, 2017 at 2:19 PM, Sivakoff, Frances <sivakoff.3 at osu.edu> wrote:
> I would like to use ggplot2 to plot the partial residuals of an indicator (0 or 1) independent variable in a generalized linear mixed model fit with a "nbinom1" family using glmmadmb. My model has a response variable that is a count, 3 explanatory variables that are continuous, and 7 indicator variables that are 0 when a particular heavy metal is not detected and 1 when it is detected above a threshold value. I'd like to plot the partial residuals of the various independent variables. I think that the model below using the Owl data would be a good example data set for how to do this. The model below has a response variable that is a count, an explanatory variables that is continuous (arrivalTime), two categorical variables (FoodTreatment and SexParent), a random effect of Nest, and uses a "nbinom1" family.
>
> ##Using the Owl Data
> om <- glmmadmb(SiblingNegotiation~FoodTreatment+ArrivalTime+SexParent+
>                  (1|Nest),family="nbinom1",data=Owls)
>
> Could you please suggest a method for plotting the partial residuals of the explanatory variables.
>
> Thank you,
> Frances
>
>
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>
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