[R-sig-ME] Is it ok to use lmer() for an ordered categorical (5 levels) response variable?

Nicolas Deguines n|codegu|ne@ @end|ng |rom gm@||@com
Thu Mar 7 14:48:41 CET 2019

Dear Emmanuel, Dimitris, Steven, Harold, Peter, Stuart and all,

I thank you for your time and for your insights into this issue; I can see
there are important things to consider and check before I further analyze
this variable. The principal components analysis is definitely my next step
to get a better idea of whether or not these four scores are correlated.

Thanks again,

On Thu, 7 Mar 2019 at 03:57, Peter Claussen <dakotajudo using mac.com> wrote:

> In the backyard: fallow area, nettles (*Urtica dioica*), ivy (*Hedera
> helix*),
> and brambles (*Rubus spp.*) are each scored one if present, and the
> naturalness index was computed as the sum of these scores.
> => it results in a 5-levels ordinal variable because it can go from 0 to 4,
> and each increase in 1 means a backyard with more features of
> 'naturalness'.
> I wonder thus if this could be modelled using a glmer() with family =
> binomial and feeding to the model two columns: cbind(sum of 1's, sum of
> 0's) (see R documentation for family{stats}, in the Details: "*As a
> two-column integer matrix: the first column gives the number of successes
> and the second the number of failures.*")
> I will try and see how the model fit the data. But I would be interested in
> getting a theoretical opinion.
> I’m not sure summing the scores is correct. Are the distributions of
> nettles, ivy and brambles independent, or could they be correlated?
> If you have a fallow area and find nettles, is it also likely to have ivy?
> If so, the the binary outcomes (nettles present and ivy present) are not
> really additive.  Similarly, are the outcomes equivalent. That is, is a
> fallow plot with nettles, and nettles only, equal in ’naturalness’ to a
> fallow plot with ivy and only ivy?
> You might want a multivariate approach. Have you considered principal
> components to reduce each set of (nettles, ivy, branbles) to a single
> score, and then analyze that score using lmer?
> Cheers,
> Peter

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