fixef.lmekin {coxme} | R Documentation |

## Extraction functions for Lmekin

### Description

Extract the fixed effects, random effects, variance of the fixed effects, or variance of the random effects from a linear mixed effects model fit with lmekin.

### Usage

```
## S3 method for class 'lmekin'
fixef(object, ...)
## S3 method for class 'lmekin'
ranef(object, ...)
## S3 method for class 'lmekin'
vcov(object, ...)
## S3 method for class 'lmekin'
VarCorr(x, ...)
## S3 method for class 'lmekin'
logLik(object, ...)
```

### Arguments

`object` |
an object inheriting from class |

`x` |
an object inheriting from class |

`...` |
some methods for this generic require additional arguments. None are used in this method. |

### Details

For the random effects model `y = X\beta + Zb + \epsilon`

, let `\sigma^2`

be the variance of the error term
`\epsilon`

.
Let `A= \sigma^2 P`

be the variance of the random effects
`b`

. There is a computational advantage to solving the problem
in terms of `P`

instead of `A`

, and that is what is
stored in the returned lmekin object.
The `VarCorr`

function returns elements of `P`

; the print
and summary functions report values of `A`

.
Pinhiero and Bates call `P`

the precision factor.

### Value

the fixed effects are a vector and vcov returns their variance/covariance matrix. The random effects are a list with one element for each random effect. The ranef component contains the coefficients and VarCorr the estimated variance/covariance matrix. The logLik method returns the loglikelihood along with its degrees of freedom.

### Author(s)

Terry Therneau

### References

J Pinheiro and D Bates, Mixed-effects models in S and S-Plus. Springer, 2000.

### See Also

`lmekin`

, `random.effects`

,
`fixed.effects`

, `link{vcov}`

, `VarCorr`

### Examples

```
data(ergoStool, package="nlme") # use a data set from nlme
efit <- lmekin(effort ~ Type + (1|Subject), ergoStool)
ranef(efit)
```

*coxme*version 2.2-20 Index]