Hierarchical multivariate covariance reaction norm modeling (Bovidae)

Knowledge graph centered on Hierarchical multivariate covariance reaction norm modeling (Bovidae) with 33 nodes and 113 connections. Top connected: Rocky Mountain Biological Laboratory, Gothic, Marmota, Yellow-bellied Marmot, Beetles.

Method synopsis

A Bayesian hierarchical model that allows phenotypic correlations between life history traits to vary continuously with environmental predictors using logit-link transformations. Accounts for both among-individual and within-individual sources of variation.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure as described in the canonical source

Steps below were extracted from the paper that introduces this protocol — Detecting context dependence in the expression of life history trade-offs (2024), Journal of Animal Ecology. Implementations in other papers (listed below) may differ.

1. Model development and mathematical formulation
   Developed hierarchical multivariate covariance reaction norm (CRN) model using logit-link transformation to model correlation coefficients as continuous functions of environmental predictors. Model structure allows among-individual correlation matrices to vary with environmental context while accounting for within-individual variation.
   Quantities: Two trait measurements per individual per environmental contextDuration: Not specifiedConditions: Mathematical modeling framework
   Equipment: Mathematical equations, Stan statistical language
2. Bayesian model implementation
   Implemented all CRN models in Stan statistical language using R interface. Used normal distributions for trait means, exponential distributions for variance parameters. Ran 3 chains with 1000 burn-in iterations, sampled 3000 iterations total. Assessed convergence using Gelman-Rubin diagnostic and visual inspection.
   Quantities: 3 MCMC chains, 1000 burn-in iterations, 3000 total iterations per chainDuration: Model runtime not specifiedConditions: Computational environment
   Equipment: Stan statistical language, R software, CmdStanR package

Typical Equipment

• Stan statistical language
• R software
• CmdStanR package

Output Measurements

• context-dependent correlation coefficients
• environmental effect sizes
• credible intervals

Papers Using This Protocol (1)

Species Studied With This Protocol

Places Where Used