simulate.lme {nlme} | R Documentation

## simulate lme models

### Description

The model `m1` is fit to the data. Using the fitted values of the parameters, `nsim` new data vectors from this model are simulated. Both `m1` and `m2` are fit by maximum likelihood (ML) and/or by restricted maximum likelihood (REML) to each of the simulated data vectors.

### Usage

    simulate.lme(m1, m2, Random.seed, method, nsim, niterEM, useGen)

### Arguments

`m1` | an object inheriting from class `lme`, representing a fitted linear mixed-effects model, or a list containing an lme model specification. If given as a list, it should contain components `fixed`, `data`, and `random` with values suitable for a call to `lme`. This argument defines the null model.
`m2` | an `lme` object, or a list, like `m1` containing a second lme model specification. This argument defines the alternative model. If given as a list, only those parts of the specification that change between model `m1` and `m2` need to be specified.
`Random.seed` | an optional vector to seed the random number generator so as to reproduce a simulation. This vector should be the same form as the `.Random.seed` object.
`method` | an optional character array. If it includes `"REML"` the models are fit by maximizing the restricted log-likelihood. If it includes `"ML"` the log-likelihood is maximized. Defaults to `c("REML", "ML")`, in which case both methods are used.
`nsim` | an optional positive integer specifying the number of simulations to perform. Defaults to 1000.
`niterEM` | an optional integer vector of length 2 giving the number of iterations of the EM algorithm to apply when fitting the `m1` and `m2` to each simulated set of data. Defaults to `c(40,200)`.
`useGen` | an optional logical value. If `TRUE`, numerical derivatives are used to obtain the gradient and the Hessian of the log-likelihood in the optimization algorithm in the `ms` function. If `FALSE`, the default algorithm in `ms` for functions that do not incorporate gradient and Hessian attributes is used. Default depends on the `pdMat` classes used in `m1` and `m2`: if both are standard classes (see `pdClasses`) then defaults to `TRUE`, otherwise defaults to `FALSE`.

### Value

an object of class `simulate.lme` with components `null` and `alt`. Each of these has components `ML` and/or `REML` which are matrices. An attribute called `Random.seed` contains the seed that was used for the random number generator.

### Author(s)

Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu

### See Also

`lme`

### Examples

    data(Orthodont)
    ## Not run:
    orthSim <-
     simulate.lme(m1 = list(fixed = distance ~ age, data = Orthodont,
                            random = ~ 1 | Subject),
                  m2 = list(random = ~ age | Subject))
    ## End(Not run)

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