fit_meta: Fit a meta-analytical model to extract global effect sizes...

In radchukv/adRes: Assessing Whether Phenotypic Changes in Response to Climate are Adaptive

Description

fit_meta fits mixed-effects meta-analytical model to extract a global effect size across the studies

Usage

fit_meta(meta_data, rand_trait = FALSE, fixed = NULL, digit = 3)

Arguments

meta_data	A dataframe with rows representing records per studies, including the effect sizes and required fixed and random effects.
rand_trait	A boolean indicating whether to include a trait type as a random effect in the model.
fixed	A string indicating the name of the fixed effect (called exactly as it is called in the dataframe meta_data) if a meta-analytic model includes a fixed predictor, and NULL (default) otherwise.
digit	An integer indicating how many digits to display on the screen.

Details

This function fits a mixed-effects meta-analytical model with appropriate residual model structure to assess the significance of an overall global effect size. Can be fit both with and without fixed effects. If fit without any fixed effects, then the overall effect size across the studies is obtained.

Value

A list of length eight, containing the results of the meta-analysis: a global slope, its SE, a full model fitted with REML, a null model fitted with ML, a global model fitted with ML, results of LRT comparing the model with the effect vs. the reduced one, the data used for the meta-analysis, and heterogeneity metrics.

Examples

## Not run: 
nb_cores <- 2L ## increase the number for using more cores
dat_sel_phen <- prepare_data(data = dat_Sel,
                             temperature = TRUE, precipitation = FALSE,
                             phenology = TRUE, morphology = FALSE)
test_sel <- extract_effects_all_ids(data = dat_sel_phen,
                                    condition = '3', nb_cores = nb_cores)
test_meta_sel <- fit_meta(test_sel)
test_meta_sel_Fitn <- fit_meta(test_sel, fixed = 'Fitness_Categ')


dat_T_phen <- prepare_data(data = dat_Trait,
                           temperature = TRUE, precipitation = FALSE,
                           phenology = TRUE, morphology = FALSE)
test_T_phen <- extract_effects_all_ids(data = dat_T_phen,
                                      condition = '2', nb_cores = nb_cores)
test_meta_T_phen <- fit_meta(test_T_phen)
test_meta_T_phen_Taxon <- fit_meta(test_T_phen, fixed = 'Taxon')

## End(Not run)

radchukv/adRes documentation built on June 1, 2019, 7:05 p.m.