rpt.remlLMM: LMM-based Repeatability Using REML

Description Usage Arguments Value Author(s) References See Also Examples

Description

Calculates repeatability from a linear mixed-effects models fitted by REML (restricted maximum likelihood).

Usage

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	rpt.remlLMM(y, groups, CI=0.95, nboot=1000, npermut=1000)

Arguments

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).

Value

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.

Author(s)

Holger Schielzeth (holger.schielzeth@ebc.uu.se) & Shinichi Nakagawa (shinichi.nakagawa@otago.ac.nz)

References

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

See Also

rpt.mcmcLMM, rpt.aov, rpt.corr, print.rpt, rpt.remlLMM.adj

Examples

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# 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)

rptR documentation built on May 2, 2019, 5:01 p.m.

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