confint.lmm: Statistical Inference for Linear Mixed Model In LMMstar: Repeated Measurement Models for Discrete Times

 confint.lmm R Documentation

Statistical Inference for Linear Mixed Model

Description

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

Usage

``````## S3 method for class 'lmm'
confint(
object,
parm = NULL,
level = 0.95,
effects = NULL,
robust = FALSE,
null = 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 errors (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. `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 some of the following coefficient (in rows):

• column estimate: the estimate.

• column se: the standard error.

• column statistic: the test statistic.

• column df: the degree of freedom.

• column lower: the lower bound of the confidence interval.

• column upper: the upper bound of the confidence interval.

• column null: the null hypothesis.

• column p.value: the p-value relative to the null hypothesis.

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

`coef.lmm` for a simpler output (e.g. only estimates).
`model.tables.lmm` for a more detailed output (e.g. with p-value).

Examples

``````#### 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)

#### Confidence intervals ####
## based on a Student's t-distribution with transformation
confint(eUN.lmm, effects = "all")
## based on a Student's t-distribution without transformation
confint(eUN.lmm, effects = "all",
transform.sigma = "none", transform.k = "none", transform.rho = "none")
## based on a Student's t-distribution transformation but not backtransformed
confint(eUN.lmm, effects = "all", backtransform = FALSE)
## based on a Normal distribution with transformation
confint(eUN.lmm, df = FALSE)

``````

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