Solved – Which method to use when calculating the confidence interval of GLMM Gamma Regression with the lme4 package in R

I am fitting a GLMM with family gamma using the lme4 package in R. Below is a code example to simulate the gamma GLMM fitting.

# Load packages library(tidyverse) library(lme4) library(lmerTest)  # Set seed set.seed(200)  # Create an example data frame dat <- data_frame(X = rgamma(500, shape = 2),                   Group = rep(c("A", "B", "C", "D", "E"), each = 100)) %>%   mutate(R = unlist(map(1:5, ~rnorm(100, .x)))) %>%   mutate(Y = exp(X + R))  # Fit a GLMM with Gamma and log link fit <- glmer(Y ~ X + (1 | Group), data = dat, family = Gamma(link = "log")) 

For poisson or binomial GLMM, we can use the confint function to calculate the confidence interval. But the default setting (method = "profile) is not working for gamma GLMM.

confint(fit) Computing profile confidence intervals ... Error in profile.merMod(object, which = parm, signames = oldNames, ...) :    can't (yet) profile GLMMs with non-fixed scale parameters 

Instead, we can set the method to be Wald or boot to calculate the confidence interval.

# Calculate the confidence interval using the Wald method confint(fit, method = "Wald") #                2.5 %   97.5 % # .sig01            NA       NA # .sigma            NA       NA # (Intercept) 2.199512 4.548215 # X           1.018495 1.131192  # Calculate the confidence interval using the boot method confint(fit, method = "boot") #                 2.5 %    97.5 % # .sig01      0.4264700 1.9473079 # .sigma      0.8331289 0.9826871 # (Intercept) 2.1469817 4.5461055 # X           1.0202349 1.1340656 # Warning message: #   In bootMer(object, FUN = FUN, nsim = nsim, ...) : #   some bootstrap runs failed (5/500) 

I am curious about which method to use and what would be the pros and cons. As far as I can tell, the Wald method is fast to compute, while the bootstrapping method takes a long time to run. But Wald method can only compute the confidence interval of the fixed-effect parameters. Any insights or suggestion would be appreciated.

Similar Posts:

• Solved – What method is used to calculate confidence intervals in R’s MASS package function confint.glm
• Solved – Understanding confidence intervals in Firth penalized logistic regression
• Solved – Calculating confidence intervals of marginal means in linear mixed models
• Solved – Confidence Interval for Inverse Gamma Distribution
• Solved – Calculate the confidence interval for the mean of a beta distribution