Description Usage Arguments Value See Also Examples
fit_cond_id
fits a mixed-effects model for a single study id in the
dataset. This model takes into account temporal autocorrelation and includes
the desired fixed-effects predictors.
1 | fit_cond_id(data, id, condition)
|
data |
A dataframe containing per each study the time series of relevant variables (i.e. yearly climate values, yearly trait values or yearly selection differentials) to be analyzed. |
id |
A character specifying the unique study id. |
condition |
A character specifying which condition is to be tested (for more details see Radchuk et al. (in review)):
|
The list of length 5. The first element is the best full
fitted model returned with the function fit_model
.
The second element contains results of LRT. The third element
is a condition tested, the forth element is a study id, and the
fifth element is a dataset to what the study belongs (PRCS or PRC).
1 2 3 4 5 6 7 8 9 10 | dat_trials <- prepare_data(data = dat_Clim,
temperature = TRUE, precipitation = FALSE,
phenology = TRUE, morphology = TRUE)
test <- fit_cond_id(data = dat_trials, id = '1', condition = '1')
dat_temp_phen <- prepare_data(data = dat_Trait,
temperature = TRUE, precipitation = FALSE,
phenology = TRUE, morphology = FALSE)
test_trait <- fit_cond_id(data = dat_temp_phen, id = '1', condition = '2')
test_trait$model
|
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