[R-sig-ME] A question about CLMM in R

[Dan McCloy]

The column labeled Pr(>|z|) is the p-value provided by ordinal::clmm
(it is also labeled this way in lme4::glmer among others).

On Thu, Dec 3, 2015 at 9:01 AM, Georgina Southon
<g.southon at sheffield.ac.uk> wrote:
> Dear CLMM experts,
>
> I have been using the ordinal package in R to model ordinal response data with CLMM, with the inclusion of categorical predictor variables and interaction terms. The model returns perfectly coherent results thankfully (a truncated example attached), however it does not provide an overall P value for each interaction term. Is this possible to obtain when modelling with clmm?
>
> Call:
> clmm2(location = preference ~ treatment + siteuse +treatment*siteuse,random+sample,Hess=TRUE
>
>
>  random = sample,
>     data = plops, Hess = TRUE)
> Random effects:
>             Var  Std.Dev
> sample 1.660947 1.288777
> Location coefficients:
>                       Estimate Std. Error z value Pr(>|z|)
> treatmentB             0.0736   1.4480     0.0508 0.95947987
> treatmentC             0.8667   1.0871     0.7972 0.42531178
> treatmentD             0.1548   1.1883     0.1303 0.89636709
> treatmentE            -0.9512   1.3482    -0.7056 0.48046420
> treatmentF             4.0151   1.2521     3.2066 0.00134313
> treatmentG            -0.0489   1.0773    -0.0454 0.96376758
> treatmentH             1.1422   1.2055     0.9474 0.34342605
> treatmentI             0.2228   1.0840     0.2055 0.83716432
> siteuse               -0.0004   0.0013    -0.3159 0.75211206
>
>
>
>
> treatmentB:siteuse     0.0012   0.0019     0.6217 0.53413206
> treatmentC:siteuse     0.0011   0.0015     0.7460 0.45565644
> treatmentD:siteuse     0.0009   0.0016     0.5841 0.55913734
> treatmentE:siteuse     0.0004   0.0016     0.2355 0.81378524
> treatmentF:siteuse     0.0002   0.0016     0.1011 0.91943399
> treatmentG:siteuse    -0.0006   0.0015    -0.4202 0.67432023
> treatmentH:siteuse     0.0000   0.0018    -0.0278 0.97782476
> treatmentI:siteuse    -0.0019   0.0016    -1.1369 0.25559690
>
>
>
> Any insights would be most gratefully received.
>
> Thank you,
>
>
> Dr Georgina Southon
> Post-doctoral Researcher
> Department of Landscape
> The University of Sheffield
>
>
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>
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