estimable: Contrasts and estimable linear functions of model coefficients
Description
Compute and test contrasts and other estimable linear
functions of model coefficients for for lm, glm, lme, lmer, and geese
objects
Usage
estimable(obj, cm, beta0, conf.int=NULL, joint.test=FALSE, show.beta0)
## S3 method for class 'lmer':
estimable(obj, cm, beta0, conf.int = NULL, show.beta0, sim.lmer = TRUE, n.sim = 1000)
Arguments
obj
Regression (lm,glm,lme,lmer) object.
cm
Vector, List, or Matrix specifying estimable linear functions or
contrasts. See below for details.
beta0
Vector of null hypothesis values
conf.int
Confidence level. If provided, confidence intervals
will be computed.
joint.test
Logical value. If TRUE a 'joint' Wald test for the
hypothesis $L \beta=\beta_0$ is performed.
Otherwise 'row-wise' tests are performed, i.e. $(L
\beta)_i=\beta_{0i}$
show.beta0
Logical value. If TRUE a column for beta0 will be
included in the output table. Defaults to TRUE when beta0 is
specified, FALSE otherwise.
sim.lmer
Logical value. If TRUE p-values and confidence intervals will be estimated using [Matrix]{mcmcsamp}.n.sim{Number of MCMC samples to take in [Matrix]{mcmcsamp}.}
estimab