confint: Statistical Inference for Linear Mixed Model

Description Usage Arguments Value See Also Examples

Description

Compute confidence intervals (CIs) and p-values for the coefficients of a linear mixed model.

Usage

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## S3 method for class 'lmm'
confint(
  object,
  parm = NULL,
  level = 0.95,
  effects = NULL,
  robust = FALSE,
  null = NULL,
  strata = NULL,
  columns = NULL,
  df = NULL,
  type.information = NULL,
  transform.sigma = NULL,
  transform.k = NULL,
  transform.rho = NULL,
  transform.names = TRUE,
  backtransform = NULL,
  ...
)

Arguments

object

a lmm object.

parm

Not used. For compatibility with the generic method.

level

[numeric,0-1] the confidence level of the confidence intervals.

effects

[character] Should the CIs/p-values for all coefficients be output ("all"), or only for mean coefficients ("mean" or "fixed"), or only for variance coefficients ("variance"), or only for correlation coefficients ("correlation").

robust

[logical] Should robust standard error (aka sandwich estimator) be output instead of the model-based standard errors. Not feasible for variance or correlation coefficients estimated by REML.

null

[numeric vector] the value of the null hypothesis relative to each coefficient.

strata

[character vector] When not NULL, only output coefficient relative to specific levels of the variable used to stratify the mean and covariance structure.

columns

[character vector] Columns to be output. Can be any of "estimate", "se", "statistic", "df", "null", "lower", "upper", "p.value".

df

[logical] Should a Student's t-distribution be used to model the distribution of the coefficient. Otherwise a normal distribution is used.

type.information, transform.sigma, transform.k, transform.rho, transform.names

are passed to the vcov method. See details section in coef.lmm.

backtransform

[logical] should the variance/covariance/correlation coefficient be backtransformed?

...

Not used. For compatibility with the generic method.

Value

A data.frame containing for each coefficient (in rows):

See Also

the function anova to perform inference about linear combinations of coefficients and adjust for multiple comparisons.

Examples

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## simulate data in the long format
set.seed(10)
dL <- sampleRem(100, n.times = 3, format = "long")

## fit Linear Mixed Model
eUN.lmm <- lmm(Y ~ X1 + X2 + X5, repetition = ~visit|id, structure = "UN", data = dL)

## based on a Student's t-distribution with transformation
confint(eUN.lmm)
## based on a Student's t-distribution without transformation
confint(eUN.lmm, transform.sigma = "none", transform.k = "none", transform.rho = "none")
## based on a Normal distribution with transformation
confint(eUN.lmm, df = FALSE)

LMMstar documentation built on Nov. 5, 2021, 1:07 a.m.