glmmTMB (version 0.2.3)

confint.glmmTMB: Calculate confidence intervals

Description

Calculate confidence intervals

Usage

# S3 method for glmmTMB
confint(object, parm, level = 0.95,
  method = c("wald", "Wald", "profile", "uniroot"),
  component = c("all", "cond", "zi", "other"), estimate = TRUE,
  parallel = c("no", "multicore", "snow"),
  ncpus = getOption("profile.ncpus", 1L), cl = NULL, ...)

Arguments

object

glmmTMB fitted object.

parm

Specification of a parameter subset after component subset has been applied.

level

Confidence level.

method

'wald', 'profile', or 'uniroot': see Details function)

component

Which of the three components 'cond', 'zi' or 'other' to select. Default is to select 'all'.

estimate

(logical) add a third column with estimate ?

parallel

method (if any) for parallel computation

ncpus

number of CPUs/cores to use for parallel computation

cl

cluster to use for parallel computation

...

arguments may be passed to profile.merMod or tmbroot

Details

Available methods are

wald

These intervals are based on the standard errors calculated for parameters on the scale of their internal parameterization depending on the family. Derived quantities such as standard deviation parameters and dispersion parameters are backtransformed. It follows that confidence intervals for these derived quantities are asymmetric.

profile

This method computes a likelihood profile for the specified parameter(s) using profile.glmmTMB; fits a spline function to each half of the profile; and inverts the function to find the specified confidence interval.

uniroot

This method uses the uniroot function to find critical values of one-dimensional profile functions for each specified parameter.

Examples

Run this code
# NOT RUN {
data(sleepstudy, package="lme4")
model <- glmmTMB(Reaction ~ Days + (1|Subject), sleepstudy)
model2 <- glmmTMB(Reaction ~ Days + (1|Subject), sleepstudy,
    dispformula= ~I(Days>8))
confint(model)  ## Wald/delta-method CIs
confint(model,parm="theta_")  ## Wald/delta-method CIs
confint(model,parm=1,method="profile")
# }

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