Estimating repeatability (intra-class correlation) from Gaussian, binary, proportion and Poisson data.
rptR provides a collection of functions for calculating point estimates, confidence intervals and significance tests of the repeatability (intra-class correlation coefficient) of measurements, as well as on the variances themselves. The function
rpt is a the core functions that calls more specialised functions as required. Specialised functions can also be called directly (see
?rpt for details). All functions return lists of values. The function
?summary.rpt produces summaries in a detailed format, whereby
?plot.rpt plots the distributions of bootstrap or permutation test estimates.
# building vignettes might take some time. Set build_vignettes = FALSE for a quick download.devtools::install_github("mastoffel/rptR", build_vignettes = TRUE)# tutorialbrowseVignettes("rptR")
Stoffel, M. A., Nakagawa, S. and Schielzeth, H. (2017), rptR: repeatability estimation and variance decomposition by generalized linear mixed-effects models. Methods Ecol Evol. 8: 1639-1644.
repeatabilities for random-slope models
update argument to update bootstraps and permutations
Progress bars for all non-parallel functions
several new sections in documentation and vignette
stability improvements for random-slope models
binary (0/1) data is now fitted without overdispersion
citation("rptR") now shows the accepted paper citation
slight improvements to the Likelihood-ratio tests
bug fix in variance addition in rptPoisson
full citation added