lmList {nlme} | R Documentation |
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 'formula'
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 |
formula |
(used in |
formula. |
Changes to the formula – see |
data |
a data frame in which to interpret the variables named in
|
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
|
na.action |
a function that indicates what should happen when the
data contain |
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 |
... |
some methods for this generic require additional arguments. None are used in this method. |
evaluate |
If |
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.
See Also
lm
,
lme.lmList
,
plot.lmList
,
pooledSD
,
predict.lmList
,
residuals.lmList
,
summary.lmList
Examples
fm1 <- lmList(distance ~ age | Subject, Orthodont)
summary(fm1)