nlme: lmList – R documentation

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lmList

List of lm Objects with a Common Model

Description

Data is partitioned according to the levels of the grouping factor g and individual lm fits are obtained for each data partition, using the model defined in object.

Usage

lmList(object, data, level, subset, na.action = na.fail,
       pool = TRUE, warn.lm = TRUE)
## S3 method for class 'lmList'
update(object, formula., ..., evaluate = TRUE)
## S3 method for class 'lmList'
print(x, pool, ...)

Arguments

`object`	For `lmList`, either a linear formula object of the form `y ~ x1+...+xn \| g` or a `groupedData` object. In the formula object, `y` represents the response, `x1,...,xn` the covariates, and `g` the grouping factor specifying the partitioning of the data according to which different `lm` fits should be performed. The grouping factor `g` may be omitted from the formula, in which case the grouping structure will be obtained from `data`, which must inherit from class `groupedData`. The method function `lmList.groupedData` is documented separately. For the method `update.lmList`, `object` is an object inheriting from class `lmList`.
`formula`	(used in `update.lmList` only) a two-sided linear formula with the common model for the individuals `lm` fits.
`formula.`	Changes to the formula – see `update.formula` for details.
`data`	a data frame in which to interpret the variables named in `object`.
`level`	an optional integer specifying the level of grouping to be used when multiple nested levels of grouping are present.
`subset`	an optional expression indicating which subset of the rows of `data` should be used in the fit. This can be a logical vector, or a numeric vector indicating which observation numbers are to be included, or a character vector of the row names to be included. All observations are included by default.
`na.action`	a function that indicates what should happen when the data contain `NA`s. The default action (`na.fail`) causes `lmList` to print an error message and terminate if there are any incomplete observations.
`pool`	an optional logical value indicating whether a pooled estimate of the residual standard error should be used in calculations of standard deviations or standard errors for summaries.
`warn.lm`	`logical` indicating if `lm()` errors (all of which are caught by `tryCatch`) should be signalled as a “summarizing” `warning`.
`x`	an object inheriting from class `lmList` to be printed.
`...`	some methods for this generic require additional arguments. None are used in this method.
`evaluate`	If `TRUE` evaluate the new call else return the call.

Value

a list of lm objects with as many components as the number of groups defined by the grouping factor. Generic functions such as coef, fixed.effects, lme, pairs, plot, predict, random.effects, summary, and update have methods that can be applied to an lmList object.

References

Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer.

Examples

fm1 <- lmList(distance ~ age | Subject, Orthodont)
summary(fm1)

nlme

Linear and Nonlinear Mixed Effects Models

v3.1-152

GPL (>= 2) | file LICENCE

Authors

José Pinheiro [aut] (S version), Douglas Bates [aut] (up to 2007), Saikat DebRoy [ctb] (up to 2002), Deepayan Sarkar [ctb] (up to 2005), EISPACK authors [ctb] (src/rs.f), Siem Heisterkamp [ctb] (Author fixed sigma), Bert Van Willigen [ctb] (Programmer fixed sigma), Johannes Ranke [ctb] (varConstProp()), R-core [aut, cre]

Initial release

2021-02-03