R: Extract lme Coefficients

coef.lme {nlme} | R Documentation

## Extract lme Coefficients

### Description

The estimated coefficients at level i are obtained by adding together the fixed effects estimates and the corresponding random effects estimates at grouping levels less or equal to i. The resulting estimates are returned as a data frame, with rows corresponding to groups and columns to coefficients. Optionally, the returned data frame may be augmented with covariates summarized over groups.

### Usage

    ## S3 method for class 'lme'
    coef(object, augFrame, level, data, which, FUN,
           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 positive integer giving the level of grouping to be used in extracting the coefficients from an object with multiple nested grouping levels. Defaults to the highest or innermost level 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 or character 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.
`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 specifying a subset
`...` | some methods for this generic require additional arguments. None are used in this method.

### Value

a data frame inheriting from class `coef.lme` with the estimated coefficients at level `level` and, optionally, other covariates summarized over groups. The returned object also inherits from classes `ranef.lme` and `data.frame`.

### Author(s)

Jose 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, New York, esp. pp. 455-457.

### See Also

`lme`, `ranef.lme`, `plot.ranef.lme`, `gsummary`

### Examples

    fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject)
    coef(fm1)
    coef(fm1, augFrame = TRUE)

[Package nlme version 3.1-104 Index]