nlme (version 3.1-164)

predict.lmList: Predictions from an lmList Object


If the grouping factor corresponding to object is included in newdata, the data frame is partitioned according to the grouping factor levels; else, newdata is repeated for all lm components. The predictions and, optionally, the standard errors for the predictions, are obtained for each lm component of object, using the corresponding element of the partitioned newdata, and arranged into a list with as many components as object, or combined into a single vector or data frame (if


# S3 method for lmList
predict(object, newdata, subset, pool, asList,, ...)


a list with components given by the predictions (and, optionally, the standard errors for the predictions) from each lm

component of object, a vector with the predictions from all

lm components of object, or a data frame with columns given by the predictions and their corresponding standard errors.



an object inheriting from class "lmList", representing a list of lm objects with a common model.


an optional data frame to be used for obtaining the predictions. All variables used in the object model formula must be present in the data frame. If missing, the same data frame used to produce object is used.


an optional character or integer vector naming the lm components of object from which the predictions are to be extracted. Default is NULL, in which case all components are used.


an optional logical value. If TRUE, the returned object is a list with the predictions split by groups; else the returned value is a vector. Defaults to FALSE.


an optional logical value indicating whether a pooled estimate of the residual standard error should be used. Default is attr(object, "pool").

an optional logical value indicating whether pointwise standard errors should be computed along with the predictions. Default is FALSE.


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


José Pinheiro and Douglas Bates

See Also

lmList, predict.lm


Run this code
fm1 <- lmList(distance ~ age | Subject, Orthodont)
predict(fm1, = TRUE)

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