[R-sig-ME] Calculating repeatability with ordinal data

[Federico Calboli]

On 2 May 2012, at 11:08, Samantha Patrick wrote:

> 
> Hi
> 
> Firstly I sent this message last week but can find no evidence that it actually sent.
> However, if this is a double posting I am very sorry.
> 
> I am currently working with repeated measures for individuals and I am
> trying to quantify individual repeatability.  Normally, for continuous
> distributions, I would use a mixed model and calculate the variance
> explained by individual divided by the total variance.  However my individual scores
> are ordinal and I have been using the clmm function in the Ordinal package:
> 
> example of data:
> ID        Bird        Sex    scoremax    year
> 622    BS8831    M       2                 2008
> 623    BS8831    M       1                 2010
> 624    BS8831    M       1                 2011
> 625    BS9065    M       1                 2010
> 626    BS9065    M       3                 2011
> 627   BS19724    F       4                 2010
> 628   BS19724    F       5                 2010
> 629   BS21302    F       1                 2010
> 630   BS25376    F       1                 2011
> 631    BS9184    F       2                 2009
> 632   BS19989    M       3                 2011
> 633   BS21617    M       4                 2008
> 634   BS21617    M       2                 2009
> 635   BS21617    M       1                 2010
> 
> where scoremax ranges from 1-5, and there are 1188 birds and 1638
> observations.
> 
> scoremax<-as.factor(scoremax)

does 

scoremax = as.ordered(scoremax)

make any difference in your results?

I ask this because as.factor() does not, strictly speaking, create an ordered factor.

BW

F




> bird<-as.factor(bird)
> year<-as.factor(year)
> fmm1<- clmm(scoremax~year+ (1|bird), link = c("probit"), Hess =TRUE)
> 
> summary(fmm1)
> 
> but this only gives the variance estimate for bird, with no residual
> estimate.  Some investigations reveal that using an ordinal regression
> in MCMCglmm will also not estimate the residual variance, and it seems
> you need to constrain this value.  I have been unable to find any posts
> about repeatability in ordinal data.
> 
> My questions I guess are:
> Is using a mixed model appropriate for calculating the repeatability of
> ordinal data (and if not does anyone know any other methods)?
> 
> If it is, does anyone have any hints on how to calculate the residual variance,
> to enable repeatability estimates to be calculated.
> 
> Many Thanks
> 
> Sam
> 
> -- 
> 
> Dr Samantha Patrick
> Post Doctoral Fellow
> Centre d'Etudes Biologiques de Chizé - CNRS
> 79360 Villiers-en-Bois
> France
> T:+33 549 097 846
> M:+33 675 603 451
> Skype: sammy_patrick
> http://www.cebc.cnrs.fr/Fidentite/patrick/patrick.htm
> http://www.researchgate.net/profile/Samantha_Patrick/
> 
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

--
Federico C. F. Calboli
Neuroepidemiology and Ageing Research
Imperial College, St. Mary's Campus
Norfolk Place, London W2 1PG

Tel +44 (0)20 75941602   Fax +44 (0)20 75943193

f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com