Hello --
I recently reran some analyses that were originally performed in Rv3.5.0 in Rv3.6.1. The marginal coefficient estimates of the models were similar, but the SEs of the marginal coefficient estimates were larger -- nearly twice as large in some cases -- when run in v3.6.1. I see from the Changelog that some changes were made to the marginal_coefs() function for faster implementation -- would this have affected the SEs? If so, which version of the function is more accurate?
Here is the structure and output of one of the models in question:
MM.egg50 <- mixed_model(fixed = Egg.egg ~ Dens.juncta.leaf + Dens.juncta.plant +
Dens.patch.50 + Plant.biomass + Patch.50.biomass + Day.of.year,
random = ~1|Cohort.ID, data = datsc, family = binomial(),
control = list(optim_method = "SANN"), nAGQ = 30)
Hello -- I recently reran some analyses that were originally performed in Rv3.5.0 in Rv3.6.1. The marginal coefficient estimates of the models were similar, but the SEs of the marginal coefficient estimates were larger -- nearly twice as large in some cases -- when run in v3.6.1. I see from the Changelog that some changes were made to the marginal_coefs() function for faster implementation -- would this have affected the SEs? If so, which version of the function is more accurate?
Here is the structure and output of one of the models in question: MM.egg50 <- mixed_model(fixed = Egg.egg ~ Dens.juncta.leaf + Dens.juncta.plant + Dens.patch.50 + Plant.biomass + Patch.50.biomass + Day.of.year, random = ~1|Cohort.ID, data = datsc, family = binomial(), control = list(optim_method = "SANN"), nAGQ = 30)
output from summary() command is identical
output from Rv3.5.0
output from Rv3.6.1
Thanks, Jessie