Knowledge graph centered on Hierarchical multivariate covariance reaction norm modeling (Bovidae) with 19 nodes and 52 connections. Top connected: Marmota flaviventris, mark-recapture (Sciuridae), Parus major, early-life trade-offs, Daphnia.
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.
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
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