R: List of lm Objects with a Common Model

lmList {lme4}

R Documentation

List of lm Objects with a Common Model

Description

List of lm Objects with a Common Model

Usage

  lmList(formula, data, family, subset, weights, na.action,
    offset, pool, ...)

Arguments

`formula`	a linear formula object of the form `y ~ x1+...+xn \| g`. 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.
`family`	an optional family specification for a generalized linear model.
`pool`	logical scalar, should the variance estimate pool the residual sums of squares
`...`	additional, optional arguments to be passed to the model function or family evaluation.
`data`	an optional data frame containing the variables named in `formula`. By default the variables are taken from the environment from which `lmer` is called. See Details.
`subset`	an optional expression indicating the subset of the rows of `data` that 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.
`weights`	an optional vector of ‘prior weights’ to be used in the fitting process. Should be `NULL` or a numeric vector.
`na.action`	a function that indicates what should happen when the data contain `NA`s. The default action (`na.omit`, inherited from the 'factory fresh' value of `getOption("na.action")`) strips any observations with any missing values in any variables.
`offset`	this can be used to specify an a priori known component to be included in the linear predictor during fitting. This should be `NULL` or a numeric vector of length equal to the number of cases. One or more `offset` terms can be included in the formula instead or as well, and if more than one is specified their sum is used. See `model.offset`.

Details

data should be a data frame (not, e.g. a groupedData object from the nlme package); use as.data.frame first to convert the data.
While data is optional, the package authors strongly recommend its use, especially when later applying methods such as update and drop1 to the fitted model (such methods are not guaranteed to work properly if data is omitted). If data is omitted, variables will be taken from the environment of formula (if specified as a formula) or from the parent frame (if specified as a character vector).

[Package lme4 version 1.1-5 Index]