intervals.lme
Confidence Intervals on lme Parameters
Description
Approximate confidence intervals for the parameters in the linear mixed-effects model represented by object
are obtained, using a normal approximation to the distribution of the (restricted) maximum likelihood estimators (the estimators are assumed to have a normal distribution centered at the true parameter values and with covariance matrix equal to the negative inverse Hessian matrix of the (restricted) log-likelihood evaluated at the estimated parameters). Confidence intervals are obtained in an unconstrained scale first, using the normal approximation, and, if necessary, transformed to the constrained scale. The pdNatural
parametrization is used for general positive-definite matrices.
Usage
## S3 method for class 'lme' intervals(object, level = 0.95, which = c("all", "var-cov", "fixed"), ...)
Arguments
object | an object inheriting from class |
level | an optional numeric value with the confidence level for the intervals. Defaults to 0.95. |
which | an optional character string specifying the subset of parameters for which to construct the confidence intervals. Possible values are |
... | some methods for this generic require additional arguments. None are used in this method. |
Value
a list with components given by data frames with rows corresponding to parameters and columns lower
, est.
, and upper
representing respectively lower confidence limits, the estimated values, and upper confidence limits for the parameters. Possible components are:
fixed | fixed effects, only present when |
reStruct | random effects variance-covariance parameters, only present when |
corStruct | within-group correlation parameters, only present when |
varFunc | within-group variance function parameters, only present when |
sigma | within-group standard deviation. |
Author(s)
José Pinheiro and Douglas Bates [email protected]
References
Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer.
See Also
lme
, intervals
, print.intervals.lme
, pdNatural
Examples
fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject) intervals(fm1)
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Licensed under the GNU General Public License.