predict.nlme {nlme} | R Documentation |

The predictions at level *i* are obtained by adding together the
contributions from the estimated fixed effects and the estimated
random effects at levels less or equal to *i* and evaluating the
model function at the resulting estimated parameters. If group values
not included in the original grouping factors are present in
`newdata`

, the corresponding predictions will be set to
`NA`

for levels greater or equal to the level at which the
unknown groups occur.

## S3 method for class 'nlme': predict(object, newdata, level, asList, na.action, naPattern, ...)

`object` |
an object inheriting from class `nlme` , representing
a fitted nonlinear mixed-effects model. |

`newdata` |
an optional data frame to be used for obtaining the predictions. All variables used in the nonlinear model, the fixed and the random effects models, as well as the grouping factors, must be present in the data frame. If missing, the fitted values are returned. |

`level` |
an optional integer vector giving the level(s) of grouping to be used in obtaining the predictions. Level values increase from outermost to innermost grouping, with level zero corresponding to the population predictions. Defaults to the highest or innermost level of grouping. |

`asList` |
an optional logical value. If `TRUE` and a single
value is given in `level` , the returned object is a list with
the predictions split by groups; else the returned value is
either a vector or a data frame, according to the length of
`level` . |

`na.action` |
a function that indicates what should happen when
`newdata` contains `NA` s. The default action
(`na.fail` ) causes the function to print an error message and
terminate if there are any incomplete observations. |

`naPattern` |
an expression or formula object, specifying which returned values are to be regarded as missing. |

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

if a single level of grouping is specified in `level`

, the
returned value is either a list with the predictions split by groups
(`asList = TRUE`

) or a vector with the predictions
(`asList = FALSE`

); else, when multiple grouping levels are
specified in `level`

, the returned object is a data frame with
columns given by the predictions at different levels and the grouping
factors.

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

fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3)) newLoblolly <- data.frame(age = c(5,10,15,20,25,30), Seed = rep(301,6)) predict(fm1, newLoblolly, level = 0:1)

[Package *nlme* version 3.1-57 Index]