R: Fit a linear mixed effects model

lmekin {coxme} | R Documentation

## Fit a linear mixed effects model

### Description

The lmekin function fits a linear mixed effects model, with random effects specified in the same structure as in the `coxme` function.

### Usage

    lmekin(formula, data, weights, subset, na.action, control,
    varlist, vfixed, vinit, method = c("ML", "REML"),
    x = FALSE, y = FALSE, model=FALSE,
    random, fixed, variance, ...)

### Arguments

`formula` | a two-sided formula with the response as the left hand side of a `~` operator and the fixed and random effects on the right.
`data` | an optional data frame containing the variables named in the `formula`.
`subset, weights, na.action` | further model specifications arguments as in `lm`; see there for details.
`control` | optional list of control options. See `coxme.control` for details.
`varlist` | the variance family to be used for each random term. If there are multiple terms it will be a list of variance functions. The default is `coxmeFull`. Alternatively it can be a list of matrices, in which case the `coxmeMlist` function is used.
`vfixed` | optional named list or vector used to fix the value of one or more of the variance terms at a constant.
`vinit` | optional named list or vector giving suggested starting values for the variance.
`method` | fit using either maximum likelihood or restricted maximum likelihood
`x` | if TRUE the X matrix (fixed effects) is included in the output object
`y` | if TRUE the y variable is included in the output object
`model` | if TRUE the model frame is included in the output object
`fixed, random, variance` | In an earlier version of `lmekin` the fixed and random effects were separate arguments. These arguments are included for backwards compatability, but are depreciated. The variance argument is a depreciated alias for vfixed.
`...` | any other arguments are passed forward to `coxme.control`.

### Details

Let A = sB be the variance matrix of the random effects where s is the residual variance for the model. Internally the routine solves for the parameters of B, computing A at the end. The `vinit` and `vfixed` parmaters refer to B, however.

It is possible to specify certain models in `lmekin` that can not be fit with lme, in particular models with familial genetic effects, i.e., a kinship matrix, and hence the name of the routine. Using user-specified variance functions an even wider range of models is possible. For simple models the specification of the random effects follows the same form as the `lmer` function. For any model which can be fit by both `lmekin` and `lmer`, the latter routine would normally be prefered due to a much wider selection of post-fit tools for residuals, prediction and plotting.

Much of the underlying model code for specification and manipulation of the random effects is shared with the `coxme` routine. In fact lmekin was originally written only to provide a test routine for those codes, and no expectation that it would find wider utility.

### Value

An object of class `lmekin`.

### Author(s)

Terry Therneau

### See Also

`lmekin.object`, `coxme`

### Examples

      data(ergoStool, package="nlme")  # use a data set from nlme
      fit1 <- lmekin(effort ~ Type + (1|Subject), data=ergoStool)
      ## Not run:
      # gives the same result
      require(nlme)
      fit2 <- lme(effort ~ Type, data=ergoStool, random= ~1|Subject,
                method="ML")

    ## End(Not run)

[Package coxme version 2.2-7 Index]