[R-sig-ME] Highly unbalanced design with count data

[Thierry Onkelinx]

Dear Adriaan,

I'd at least add a year random intercept to take into account generic time
effects. glmer(response ~ Status + (1|Site) + (1|Year), family=poisson) Such
model assumes that a "status" has a constant relative effect which is
identical on all sites. One could argue that the length of a disturbance is
important too. E.g. the bird will return if the disturbance is short but
will stay away when the distrubance is longer. However, I doubt that you
have sufficient data to fit such model.

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

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Op ma 11 feb. 2019 om 10:07 schreef Adriaan De Jong <Adriaan.de.Jong using slu.se
>:

> Dear list members,
> Birds in agricultural landscapes have been counted annually in a
> Before-During-After Control-Impact study of possible effects from the
> construction of a new railway. Obviously, much of the “design” of this
> experiment was beyond my control; you cannot direct a billion € project for
> the sake of a bird study ☺ There are six control sites and 13 impact sites
> of different sizes and shapes (because that’s what the landscape had to
> offer). All impacted patches of agricultural land were included. Counts
> were made 2002-2015 with a gap for 2011 and 2012. The construction of the
> railway became a lengthy process that occurred in various sections along
> the full 190 km. The sequential steps in the process were: Before,
> Construction (when the actual building took place), Ready (when the railway
> was ready but no trains were running) and Traffic (when regular train
> traffic occurred). Each impact site (patch of agricultural land) was
> subject for these steps during various years and durations. Also, not all
> impact sites were surveyed during all the steps. There are issues in the
> data structure of the count data (some over- and under-dispersion, and high
> proportion of zero counts), but my main concern is the irregular temporal
> structure of “treatments” (variable Status below). The citation marks
> around the word treatment is because these are not independent treatments
> but rather repeated measures in a fixed sequence. It would be lovely to
> “digest” the full dataset with a Poisson GLMM of some sort, e.g.
> glmer(response ~ Status + (1|Site), family=poisson), but I have a strong
> feeling that the requirements of such an analysis are violated by the
> highly unbalanced design. I’ve also considered a repeated measures ANOVA
> but I assume the same problem applies there.
> I would appreciate any comments or advice that could bring the analysis of
> this dataset further. Thanks in advance!
> Have a nice day!
> Adjan
>
> Adriaan “Adjan” de Jong
> Senior researcher
> Dept of Wildlife, Fish, and Environmental Studies
> Swedish University of Agricultural Sciences
>
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