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

A wrapper function for (adjusted) repeatability calculations. Calls specialised functions depending of the choice of datatype and method.

1 2 3 4 5 |

`formula` |
Formula as used e.g. by lmer. The grouping factor of interest needs to be included as a random effect, e.g. '(1|groups)'. Covariates and additional random effects can be included to estimate adjusted repeatabilities. |

`grname` |
A character string or vector of character strings giving the name(s) of the grouping factor(s), for which the repeatability should be estimated. Spelling needs to match the random effect names as given in |

`data` |
A dataframe that contains the variables included in the formula argument. |

`datatype` |
Character string specifying the data type ("Gaussian", "binomial", "proportion", "count"). "binomial" and "proportion" are interchangable and call the same functions. |

`method` |
character string specifying the method of calculation. Defaults to "REML" for Gaussian data and to "GLMM.multi" for binomial and count data. |

`link` |
Character string specifying the link function. Ignored for "Gaussian" datatype and for the "GLMM.add" method. |

`CI` |
Width of the confidence interval between 0 and 1 (defaults to 0.95). |

`nboot` |
Number of bootstrapping runs used when calculating the asymtotic confidence interval (defaults to 1000). Ignored for the "GLMM.add", "corr" and "ANOVA" methods. |

`npermut` |
Number of permutations used when calculating asymtotic |

For `datatype="Gaussian"`

calls function rpt.remlLMM.adj or rpt.mcmcLMM.adj (methods "REML" and "MCMC", respecitvely) (Note that rpt.mcmcLMM.adj is not yet implemented).

Returns an object of class rpt. See details for specific functions.

`datatype` |
Type of repsonse ("Gaussian", "binomial" or "count"). |

`method` |
Method used to calculate repeatability ("REML", "MCMC", "ANOVA", "corr", "GLMM.add" or "GLMM.multi"). |

`link` |
Link functions used (GLMMs only). |

`CI` |
Width of the confidence interval or Bayesian credibility interval. |

`R` |
Point estimate for repeatability. |

`R.link` |
Point estimate for repeatability on link scale (GLMM only). |

`R.org` |
Point estimate for repeatability on original scale (GLMM only). |

`se` |
Standard error ( |

`se.link` |
Standard error ( |

`se.org` |
Standard error ( |

`CI.R` |
Confidence interval or Bayesian credibility interval for the repeatability. |

`CI.link` |
Confidence interval or Bayesian credibility interval for repeatability on link scale (GLMM only). |

`CI.org` |
Confidence interval or Bayesian credibility interval for repeatability on original scale (GLMM only). |

`P` |
Significace test, returned as |

`P.link` |
Significace test for repeatability on link scale, returned as |

`P.org` |
Significace test for repeatability on original scale, returned as |

`R.post` |
MCMC samples form the posterior distributions of |

`R.boot` |
Parametric bootstrap samples for |

`R.permut` |
Permutation samples for |

Holger Schielzeth ([email protected]) & Shinichi Nakagawa ([email protected])

Nakagawa, S. and Schielzeth, H. (2011) *Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists*. Biological Reviews 85: 935-956.

rpt

1 2 3 4 5 6 7 8 9 | ```
# for Gaussian data - correlation-based repeatability
# repeatability for male breeding success on a transformed scale
data(Fledglings)
Fledglings$sqrtFledge <- sqrt(Fledglings$Fledge)
(rpt.Fledge <- rpt.adj(sqrtFledge ~ Age + (1|MaleID), "MaleID", data=Fledglings, datatype="Gaussian",
method="REML", nboot=10, npermut=10)) # reduced number of nboot and npermut iterations
# data(BodySize)
# (rpt.Weight <- rpt.adj(Weight ~ Sex + (1|BirdID), "BirdID", data=BodySize, datatype="Gaussian",
# method="MCMC"))
``` |

rptR documentation built on May 31, 2017, 2:53 a.m.

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