Candidate calibration models

The family of logistic calibration models compared by compare_calibration_models(), from a single logistic regression on the logit of the confidence score to a binomial GLMM with random slopes by species and a site x species intercept.

Usage

calibration_models(uncorrelated = FALSE, single_species = FALSE)

Arguments

uncorrelated

Add m5_species_x_site_uncorrelated, the m4 structure without the correlation between the species intercepts and slopes. It avoids the singular fits of m4 when that correlation is estimated at +-1. FALSE keeps the candidates of 2.0.0.

single_species

Use a family for one species: global logistic regression, a site intercept, and a site intercept and slope. With uncorrelated = TRUE, also include independent site intercepts and slopes. FALSE preserves the multispecies family.

Value

A named list of formulas: m0_global, m1_species_intercept, m2_species_slope, m3_plus_site, m4_species_x_site and, with uncorrelated = TRUE, m5_species_x_site_uncorrelated. With single_species = TRUE: m0_global, m1_site_intercept, m2_site_slope and optionally m3_site_slope_uncorrelated.

Details

The list goes from the simplest to the most complex model; that order is the complexity used by select_calibration_model().