Confidence intervals for model parameters
Usage
# S3 method for class 'galamm'
confint(object, parm, level = 0.95, method = "Wald", ...)
Arguments
- object
An object of class
galamm
returned fromgalamm
.- parm
Parameters for which to compute intervals. Use
"theta"
to get all variance parameters,"beta"
to get all fixed regression coefficients,"lambda"
to get all factor loadings, and"weights"
to get all weights. The parameter can also be given as a numeric vector with indices specifying the parameters. When given as characters, the arguments are case sensitive.- level
Decimal number specifying the confidence level. Defaults to 0.95.
- method
Character of length one specifying the type of confidence interval. Currently only "Wald" is available. The argument is case sensitive.
- ...
Other arguments passed on to other methods. Currently not used.
See also
fixef.galamm()
for fixed effects, coef.galamm()
for coefficients
more generally, and vcov.galamm()
for the variance-covariance matrix.
confint()
is the generic function.
Other details of model fit:
VarCorr()
,
coef.galamm()
,
deviance.galamm()
,
factor_loadings.galamm()
,
family.galamm()
,
fitted.galamm()
,
fixef()
,
formula.galamm()
,
llikAIC()
,
logLik.galamm()
,
nobs.galamm()
,
predict.galamm()
,
print.VarCorr.galamm()
,
ranef.galamm()
,
residuals.galamm()
,
response()
,
sigma.galamm()
,
vcov.galamm()
Examples
# Poisson GLMM
count_mod <- galamm(
formula = y ~ lbas * treat + lage + v4 + (1 | subj),
data = epilep, family = poisson
)
confint(count_mod, parm = "beta", level = .99)
#> 0.5 % 99.5 %
#> (Intercept) 1.5239392 2.06319914
#> lbas 0.5471847 1.22182317
#> treat -0.7155511 0.04562592
#> lage -0.4081356 1.37730585
#> v4 -0.3016653 -0.02050959
#> lbas:treat -0.1843249 0.86110474