Description Usage Arguments Value Author(s) References See Also Examples
Calculates repeatability from a linear mixed-effects models fitted by REML (restricted maximum likelihood).
1 | rpt.remlLMM(y, groups, CI=0.95, nboot=1000, npermut=1000)
|
y |
Vector of a response values. |
groups |
Vector of group identities. |
CI |
Width of the confidence interval (defaults to 0.95). |
nboot |
Number of parametric bootstraps for interval estimation. Defaults to 1000. Larger numbers of permutations give a better asymtotic CI, but may be very time-consuming. |
npermut |
Number of permutations used when calculating asymptotic P values (defaults to 1000). |
Returns an object of class rpt that is a a list with the following elements:
datatype |
Response distribution (here: "Gaussian"). |
method |
Method used to calculate repeatability (here: "REML"). |
CI |
Width of the confidence interval. |
R |
Point estimate for repeatability. |
se |
Approximate standard error (se) for repeatability. Note that the distribution might not be symmetrical, in which case the se is less informative. |
CI.R |
Confidence interval for repeatability. |
P |
Approximate P value from a significance test based on permutation. |
R.boot |
Parametric bootstrap samples for R. |
R.permut |
Permutation samples for R. |
Holger Schielzeth (holger.schielzeth@ebc.uu.se) & Shinichi Nakagawa (shinichi.nakagawa@otago.ac.nz)
Carrasco, J. L. and Jover, L. (2003). Estimating the generalized concordance correlation coefficient through variance components. Biometrics 59: 849-858.
Faraway, J. J. (2006). Extending the linear model with R. Boca Raton, FL, Chapman & Hall/CRC.
Nakagawa, S. and Schielzeth, H. (2010) Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists. Biological Reviews 85: 935-956
rpt.mcmcLMM, rpt.aov, rpt.corr, print.rpt, rpt.remlLMM.adj
1 2 3 4 5 6 7 8 9 10 11 12 13 | # repeatability estimation for tarsus length - a very high R
data(BodySize)
attach(BodySize)
(rpt.BS <- rpt.remlLMM(Tarsus, BirdID, nboot=10, npermut=10))
# reduced number of nboot and npermut iterations
detach(BodySize)
# repeatability estimation for weight (body mass) - a lower R than the previous one
data(BodySize)
attach(BodySize)
(rpt.Weight <- rpt.remlLMM(Weight, BirdID, nboot=10, npermut=10))
# reduced number of nboot and npermut iterations
detach(BodySize)
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