confint.mlmm: Confidence Intervals for Multiple Linear Mixed Model.

In LMMstar: Repeated Measurement Models for Discrete Times

Confidence Intervals for Multiple Linear Mixed Model.

Description

Compute confidence intervals for several linear mixed models.

Usage

## S3 method for class 'mlmm'
confint(
  object,
  parm = NULL,
  level = 0.95,
  method = NULL,
  ordering = "parameter",
  ...
)

Arguments

object	an mlmm object, output of mlmm.
parm	Not used. For compatibility with the generic method.
level	[numeric,0-1] the confidence level of the confidence intervals.
method	[character] type of adjustment for multiple comparisons: one of "none", "bonferroni", "single-step", "single-step2", or "pool".
ordering	[character] should the output be ordered by type of parameter (parameter) or by model (by). Only relevant for mlmm objects.
...	other arguments are passed to confint.Wald_lmm.

Details

Statistical inference following pooling is performed according to Rubin's rule whose validity requires the congeniality condition of Meng (1994).

References

Meng X. L.(1994). Multiple-imputation inferences with uncongenial sources of input. Statist. Sci.9, 538–58.

LMMstar documentation built on Nov. 9, 2023, 1:06 a.m.