Linear mixed-effects variance partitioning (Bovidae)

Knowledge graph centered on Linear mixed-effects variance partitioning (Bovidae) with 22 nodes and 91 connections. Top connected: Rocky Mountain Biological Laboratory, Marmota, Yellow-bellied Marmot, Crested Butte, birds and mammals.

Method synopsis

Statistical approach using linear mixed-effect models to partition variance in repeated morphometric measurements into individual, temporal, and measurement error components. Includes resampling analysis to determine optimal sampling effort.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure from a recent peer-reviewed implementation

Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — Detecting between-individual differences in hind-foot length in populations of wild animals (2013), Canadian Journal of Zoology. Implementations in other papers (listed below) may differ.

1. Statistical analysis of measurement error
   Fitted linear mixed-effect models for each species with individual identity and year as random effects. Partitioned variance into individual, year, and residual components. Used restricted maximum likelihood and likelihood ratio tests to assess significance.
   Quantities: Models fitted separately for each of 3 speciesDuration: Post-collection analysisConditions: Only adult animals ≥4 years with ≥2 measurements included
   Equipment: R software, lme4 package

Typical Equipment

• R software
• lme4 package

Output Measurements

• variance components
• repeatability estimates
• measurement error quantification

Papers Using This Protocol (1)

Species Studied With This Protocol

Places Where Used