Repeatability Estimation for Gaussian and Non-Gaussian Data

Estimating repeatability (intra-class correlation) from Gaussian, binary, proportion and count data.


Build Status CRAN total downloads

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.

  • get the latest development version from github with
    # building vignettes might take some time. Set build_vignettes = FALSE for a quick download.
    devtools::install_github("mastoffel/rptR", build_vignettes = TRUE)
    # tutorial
    browseVignettes("rptR")

Citation

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.

doi

News

rptR 0.9.1

Improvements

  • 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

rptR 0.9.2

  • 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

rptR 0.9.21

  • bug fix in variance addition in rptPoisson

  • full citation added

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("rptR")

0.9.21 by Martin Stoffel, 4 months ago


Browse source code at https://github.com/cran/rptR


Authors: Martin Stoffel <[email protected]>, Shinichi Nakagawa <[email protected]>, Holger Schielzeth <[email protected]>


Documentation:   PDF Manual  


GPL (>= 2) license


Imports methods, stats, lme4, parallel, pbapply

Suggests testthat, knitr, rmarkdown


Imported by aniDom.


See at CRAN