Description Usage Arguments Details Value Author(s) References See Also Examples
Calculates repeatability from a generalised linear mixed-effects models fitted by MCMC for count data.
1 | rpt.poisGLMM.add(y, groups, CI=0.95, prior=NULL, verbose=FALSE, ...)
|
y |
Vector of a response values. |
groups |
Vector of group identities. |
CI |
Width of the Bayesian credible interval (defaults to 0.95). |
prior |
List of prior values passed to MCMCglmm function in MCMCglmm (see there for more details). Default priors will be used if prior is null. |
verbose |
Whether or not MCMCglmm should print MH diagnostics are printed to screen. Defaults to FALSE. |
... |
Additonal arguements that are passed on to MCMCglmm (e.g. length of chain, thinning interval). |
Models are fitted using the MCMCglmm function in MCMCglmm with poisson
family.
Models for binary data are fitted with list(R=list(V=1e-10,nu=-1),G=list(G1=list(V=1,nu=1,alpha.mu=0,alpha.V=25^2)))
unless other priors are specified in the call.
Returns an object of class rpt that is a a list with the following elements:
datatype |
Type of response (here: count). |
method |
Method used to calculate repeatability (here: MCMC). |
CI |
Width of the Bayesian credibility interval. |
R.link |
Point estimate for repeatability on the link scale, i.e. the mode of the posterior distribution. |
se.link |
Standard error (se) for the repeatability on the link scale, i.e. the standard deviation of the posterior distribution. Note that the distribution might not be symmetrical, in which case se is less informative. |
CI.link |
Bayesian credibility interval for the repeatability on the link scale based on the posterior distribution of R. |
P.link |
Significance test for the link scale repeatability, returned as |
R.org |
Point estimate for repeatability on the original scale, i.e. the mode of the posterior distribution. |
se.org |
Standard error (se) for repeatability on the original scale, i.e. the standard deviation of the posterior distribution. Note that the distribution might not be symmetrical, in which case se is less informative. |
CI.org |
Bayesian credibility interval for repeatability on the original scale based on the posterior distribution of R. |
P.org |
Significance test for the original scale repeatability, returned as |
R.post |
Named list of MCMC samples form the posterior distributions. |
Holger Schielzeth (holger.schielzeth@ebc.uu.se) & Shinichi Nakagawa (shinichi.nakagawa@otago.ac.nz)
Carrasco, J. L. (2010). A generalized concordance correlation coefficient based on the variance components generalized linear mixed models with application to overdispersed count data. Biometrics 66: 897-904.
Carrasco, J. L. and Jover, L. (2005). Concordance correlation coefficient applied to discrete data. Statistics in Medicine 24: 4021-4034.
Nakagawa, S. and Schielzeth, H. (2010) Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists. Biological Reviews 85: 935-956.
rpt.poisGLMM.multi, rpt, print.rpt
1 2 3 4 5 6 7 8 9 10 11 | # repeatability for female clutch size over two years.
data(BroodParasitism)
attach(BroodParasitism)
(rpt.Host <- rpt.poisGLMM.add(OwnClutches, FemaleID))
detach(BroodParasitism)
# repeatability for male fledgling success
data(Fledglings)
attach(Fledglings)
(rpt.Fledge <- rpt.poisGLMM.add(Fledge, MaleID))
detach(Fledglings)
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