#### updates models
library(vullioud2018)
data(d1)
# head(d1)
#########################################
### Creating the different datasets ###
#########################################
### As each set of models require a different focal individual,
### the datasets had to be reframed. Simillarily, as models were fitted
### separately for intra-sex and inter-sex interactions, differents datasets
### were computed.
### first we subsetted the main dataset between intra and inter-sex interactions
data_same_sex <- prepare_same_sex(d1)
data_diff_sex <- prepare_different_sex(d1)
### Aditionnaly we created a subset for the SI models testing the interactions in which
### the focal individual is a migrant with higher social support in interclan
### interaction.
data_resid <- prepare_resid(d1)
### each models has a different dataset: they were created as follow:
### SOCIAL SUPPORT MODELS: higest social support as focal
same_sex_social <- create_DF_social(data_same_sex)
diff_sex_social <- create_DF_social(data_diff_sex)
resid_social <- create_DF_social(data_resid)
### BODY MASS MODELS: higest body mass as focal
diff_sex_weight <- create_DF_weight(data_diff_sex)
same_sex_weight <- create_DF_weight(data_same_sex)
### SEX MODEL females as focal:
diff_sex_sex <- create_DF_sex(data_diff_sex)
###### MODELS #########################
#### mod1
mod_social_null_diff_PQL <- fit_social(fit_method = "PQL",
model = "null",
DF1 = diff_sex_social)
save(mod_social_null_diff_PQL, file = "mod_social_null_diff_PQL.rda", compress = "xz")
#### mod2
mod_social_null_same_PQL <- fit_social(fit_method = "PQL",
model = "null",
DF1 = same_sex_social)
save(mod_social_null_same_PQL, file = "mod_social_null_same_PQL.rda", compress = "xz")
#### mod3
### BODY MASS MODELS:
mod_mass_null_same_PQL <- fit_body_mass(fit_method = "PQL",
model = "null",
DF1 = same_sex_weight)
save(mod_mass_null_same_PQL, file = "mod_mass_null_same_PQL.rda", compress = "xz")
###mod4
mod_mass_null_diff_PQL <- fit_body_mass(fit_method = "PQL",
model = "null",
DF1 = diff_sex_weight)
save(mod_mass_null_diff_PQL, file = "mod_mass_null_diff_PQL.rda", compress = "xz")
### SEX MODELS:
mod_sex_null_diff_PQL <- fit_sex(fit_method = "PQL",
model = "null",
DF1 = diff_sex_sex)
save(mod_sex_null_diff_PQL, file = "mod_sex_null_diff_PQL.rda", compress = "xz")
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