`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`

.

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

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

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.

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.

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

`lm`

,
`lme.lmList`

,
`plot.lmList`

,
`pooledSD`

,
`predict.lmList`

,
`residuals.lmList`

,
`summary.lmList`

```
# NOT RUN {
fm1 <- lmList(distance ~ age | Subject, Orthodont)
summary(fm1)
# }
```

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