Extract lme Random Effects

ranef.lme {nlme}

R Documentation

Extract lme Random Effects

Description

The estimated random effects at level i are represented as a data frame with rows given by the different groups at that level and columns given by the random effects. If a single level of grouping is specified, the returned object is a data frame; else, the returned object is a list of such data frames. Optionally, the returned data frame(s) may be augmented with covariates summarized over groups.

Usage

## S3 method for class 'lme'
ranef(object, augFrame, level, data, which, FUN,
      standard, omitGroupingFactor, subset, ...)

Arguments

`object`	an object inheriting from class `"lme"`, representing a fitted linear mixed-effects model.
`augFrame`	an optional logical value. If `TRUE`, the returned data frame is augmented with variables defined in `data`; else, if `FALSE`, only the coefficients are returned. Defaults to `FALSE`.
`level`	an optional vector of positive integers giving the levels of grouping to be used in extracting the random effects from an object with multiple nested grouping levels. Defaults to all levels of grouping.
`data`	an optional data frame with the variables to be used for augmenting the returned data frame when `augFrame = TRUE`. Defaults to the data frame used to fit `object`.
`which`	an optional positive integer vector specifying which columns of `data` should be used in the augmentation of the returned data frame. Defaults to all columns in `data`.
`FUN`	an optional summary function or a list of summary functions to be applied to group-varying variables, when collapsing `data` by groups. Group-invariant variables are always summarized by the unique value that they assume within that group. If `FUN` is a single function it will be applied to each non-invariant variable by group to produce the summary for that variable. If `FUN` is a list of functions, the names in the list should designate classes of variables in the frame such as `ordered`, `factor`, or `numeric`. The indicated function will be applied to any group-varying variables of that class. The default functions to be used are `mean` for numeric factors, and `Mode` for both `factor` and `ordered`. The `Mode` function, defined internally in `gsummary`, returns the modal or most popular value of the variable. It is different from the `mode` function that returns the S-language mode of the variable.
`standard`	an optional logical value indicating whether the estimated random effects should be "standardized" (i.e. divided by the estimate of the standard deviation of that group of random effects). Defaults to `FALSE`.
`omitGroupingFactor`	an optional logical value. When `TRUE` the grouping factor itself will be omitted from the group-wise summary of `data` but the levels of the grouping factor will continue to be used as the row names for the returned data frame. Defaults to `FALSE`.
`subset`	an optional expression indicating for which rows the random effects should be extracted.
`...`	some methods for this generic require additional arguments. None are used in this method.

Value

a data frame, or list of data frames, with the estimated random effects at the grouping level(s) specified in level and, optionally, other covariates summarized over groups. The returned object inherits from classes random.effects.lme and data.frame.

Author(s)

José Pinheiro and Douglas Bates bates@stat.wisc.edu

References

Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer, esp. pp. 100, 461.

Examples

fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject)
ranef(fm1)
random.effects(fm1)             # same as above
random.effects(fm1, augFrame = TRUE)

[Package nlme version 3.1-139 Index]