Confidence intervals for a mixeff LMM

method = "asymptotic" (the default; synonyms "wald" and lme4's "Wald") gives Wald intervals for the fixed effects from the stored standard errors. method = "profile" gives profile-likelihood intervals with lme4's rows and names: .sig01, .sig02, ... (random-effect standard deviations and correlations, numbered as lme4 >= 2.0 does: term by term, each term's standard deviations before its correlations), .sigma, then the fixed effects. As in lme4, every fit is profiled on the ML deviance: a REML fit's intervals are those of its ML refit. The engine's relative-Cholesky theta1, ... intervals (on the fit's own criterion) are kept in attr(ci, "mm_profile")$table and can be requested by name through parm. When one parameter's profile is irregular (non-monotone, not bracketing the estimate, or a failed refit), its undetermined bounds are NA – lme4 would warn and interpolate linearly, often reporting [-1, 1] for a correlation – and the reason is in attr(ci, "mm_profile")$table (status, reason_code, reason); printing the result adds a note. See profile.mm_lmm(). method = "bootstrap" (lme4's "boot") gives parametric-bootstrap intervals for the fixed effects, controlled by bootstrap_control().

Usage

# S3 method for class 'mm_lmm'
confint(
  object,
  parm,
  level = 0.95,
  method = c("asymptotic", "wald", "bootstrap", "profile"),
  bootstrap = NULL,
  interval = c("percentile", "basic"),
  threads = 1L,
  ...
)

Arguments

object

A fitted mm_lmm.

parm

Parameters to report: names (fixed-effect names, and for "profile" also ".sig01", ..., ".sigma", "theta1", ...), lme4's "theta_" / "beta_" shortcuts ("profile" only), or indices. Defaults to all fixed effects (all lme4 rows for "profile").

level

Confidence level.

method

"asymptotic", "wald", "bootstrap", or "profile".

bootstrap

Optional bootstrap_control() for method = "bootstrap" (its threads field sets the bootstrap's worker threads).

interval

Bootstrap interval type, "percentile" or "basic".

threads

Worker threads for method = "profile" (default 1). The per-parameter profiles run concurrently; the result is identical for every value. The default is 1 because CRAN policy limits packages to at most two threads unless the user explicitly asks for more; passing threads is that request.

...

Unused.

Value

An mm_confint matrix of lower/upper bounds.

Details

lme4's confint.merMod() defaults to method = "profile"; mixeff keeps the Wald default because the profile refits the model many times (about the cost of lme4's profile; several seconds for a modest model) and can refuse on near-singular fits, while the Wald route is free. Request method = "profile" to reproduce lme4's default output.

Examples

set.seed(1)
d <- data.frame(g = factor(rep(1:10, each = 6)), x = rnorm(60))
d$y <- 1 + 0.5 * d$x + rnorm(10)[d$g] + rnorm(60)
fit <- lmm(y ~ x + (1 | g), d, control = mm_control(verbose = -1))
confint(fit)
#> Confidence intervals:
#>                 2.5 %    97.5 %
#> (Intercept) 0.7432779 2.2179314
#> x           0.3087413 0.8061215
#> method: wald_asymptotic_from_stored_standard_errors
#> status: Wald (asymptotic) intervals from stored standard errors (engine-certified profile intervals: method = "profile")
confint(fit, method = "profile")
#> Confidence intervals:
#>                 2.5 %    97.5 %
#> .sig01      0.6951562 1.8545088
#> .sigma      0.6630609 0.9829297
#> (Intercept) 0.7087136 2.2526274
#> x           0.3069545 0.8087305
#> method: profile_likelihood
#> status: available