comparePred {nlme} | R Documentation |

Predicted values are obtained at the specified values of
`primary`

for each object. If either `object1`

or
`object2`

have a grouping structure
(i.e. `getGroups(object)`

is not `NULL`

), predicted values
are obtained for each group. When both objects determine groups, the
group levels must be the same. If other covariates besides
`primary`

are used in the prediction model, their group-wise averages
(numeric covariates) or most frequent values (categorical covariates)
are used to obtain the predicted values. The original observations are
also included in the returned object.

comparePred(object1, object2, primary, minimum, maximum, length.out, level, ...)

`object1,object2` |
fitted model objects, from which predictions can
be extracted using the `predict` method. |

`primary` |
an optional one-sided formula specifying the primary
covariate to be used to generate the augmented predictions. By
default, if a covariate can be extracted from the data used to generate
the objects (using `getCovariate` ), it will be used as
`primary` . |

`minimum` |
an optional lower limit for the primary
covariate. Defaults to `min(primary)` . |

`maximum` |
an optional upper limit for the primary
covariate. Defaults to `max(primary)` . |

`length.out` |
an optional integer with the number of primary covariate values at which to evaluate the predictions. Defaults to 51. |

`level` |
an optional integer specifying the desired prediction level. Levels increase from outermost to innermost grouping, with level 0 representing the population (fixed effects) predictions. Only one level can be specified. Defaults to the innermost level. |

`...` |
some methods for the generic may require additional arguments. |

a data frame with four columns representing, respectively, the values
of the primary covariate, the groups (if `object`

does not have a
grouping structure, all elements will be `1`

), the predicted or
observed values, and the type of value in the third column: the
objects' names are used to classify the predicted values and
`original`

is used for the observed values. The returned object
inherits from classes `comparePred`

and `augPred`

.

This function is generic; method functions can be written to handle
specific classes of objects. Classes which already have methods for
this function include: `gls`

, `lme`

, and `lmList`

.

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

fm1 <- lme(distance ~ age * Sex, data = Orthodont, random = ~ age) fm2 <- update(fm1, distance ~ age) comparePred(fm1, fm2, length.out = 2)

[Package *nlme* version 3.1-57 Index]