`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 formula
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, ...)

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.

- 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.

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`

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

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