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car

brief

Print Abbreviated Ouput

Description

Print data objects and statistical model summaries in abbreviated form.

Usage

brief(object, ...)

## S3 method for class 'data.frame'
brief(object, rows = if (nr <= 10) c(nr, 0) else c(3, 2),
    cols, head=FALSE, tail=FALSE, elided = TRUE,
    classes = inherits(object, "data.frame"), ...)
## S3 method for class 'matrix'
brief(object, rows = if (nr <= 10) c(nr, 0) else c(3, 2), ...)

## S3 method for class 'numeric'
brief(object, rows = c(2, 1), elided = TRUE, ...)
## S3 method for class 'integer'
brief(object, rows = c(2, 1), elided = TRUE, ...)
## S3 method for class 'character'
brief(object, rows = c(2, 1), elided = TRUE, ...)
## S3 method for class 'factor'
brief(object, rows=c(2, 1), elided=TRUE, ...)

## S3 method for class 'list'
brief(object, rows = c(2, 1), elided = TRUE, ...)

## S3 method for class 'function'
brief(object, rows = c(5, 3), elided = TRUE, ...)

## S3 method for class 'lm'
brief(object,  terms = ~ .,
    intercept=missing(terms), pvalues=FALSE,
    digits=3, horizontal=TRUE, vcov., ...)

## S3 method for class 'glm'
brief(object, terms = ~ .,
    intercept=missing(terms), pvalues=FALSE,
    digits=3, horizontal=TRUE, vcov., dispersion, exponentiate, ...)

## S3 method for class 'multinom'
brief(object, terms = ~ .,
    intercept=missing(terms), pvalues=FALSE,
    digits=3, horizontal=TRUE, exponentiate=TRUE, ...)

## S3 method for class 'polr'
brief(object, terms = ~ .,
    intercept, pvalues=FALSE,
    digits=3, horizontal=TRUE, exponentiate=TRUE, ...)

## Default S3 method:
brief(object, terms = ~ .,
    intercept=missing(terms), pvalues=FALSE,
    digits=3, horizontal=TRUE, ...)

Arguments

`object`	a data or model object to abbreviate.
`rows`	for a matrix or data frame, a 2-element integer vector with the number of rows to print at the beginning and end of the display; for a vector or factor, the number of lines of output to show at the beginning and end; for a list, the number of elements to show at the beginning and end; for a function, the number of lines to show at the beginning and end.
`cols`	for a matrix or data frame, a 2-element integer vector with the number of columns to print at the beginning (i.e., left) and end (right) of the display.
`head, tail`	alternatives to the `rows` argument; if `TRUE`, print the first or last 6 rows; can also be the number of the first or last few rows to print; only one of `heads` and `tails` should be specified; ignored if `FALSE` (the default).
`elided`	controls whether to report the number of elided elements, rows, or columns; default is `TRUE`.
`classes`	show the class of each column of a data frame at the top of the column; the classes are shown in single-character abbreviated form—e.g., `[f]` for a factor, `[i]` for an integer variable, `[n]` for a numeric variable, `[c]` for a character variable.
`terms`	a one-sided formula giving the terms to summarize; the default is `~ .`—i.e., to summarize all terms in the model.
`intercept`	whether or not to include the intercept; the default is `TRUE` unless the `terms` argument is given, in which case the default is `FALSE`; ignored for `polr` models.
`pvalues`	include the p-value for each coefficient in the table; default is `FALSE`.
`exponentiate`	for a `"glm"` or `"glmerMod"` model using the `log` or `logit` link, or a `"polr"` or `"multinom"` model, show exponentiated coefficient estimates and confidence bounds.
`digits`	significant digits for printing.
`horizontal`	if `TRUE` (the default), orient the summary produced by `brief` horizontally, which typically saves space.
`dispersion`	see `summary.glm`
`vcov.`	either a matrix giving the estimated covariance matrix of the estimates, or a function that when called with `object` as an argument returns an estimated covariance matrix of the estimates. The default `vcov. = vcov(object, complete=FALSE)` uses the usual estimated covariance matrix with NA for any row and column with aliased regressors. Other choices include the functions documented at `hccm`, and a bootstrap estimate `vcov.=vcov(Boot(object))`; see the documentation for `Boot`. For the `glm` method, if the `vcov.` or `dispersion` argument is specified, then Wald-based confidence limits are computed; otherwise the reported confidence limits are computed by profiling the likelihood. NOTES: (1) The `dispersion` and `vcov.` arguments may not both be specified. (2) Setting `vcov.=vcov` returns an error if the model includes aliased terms; use `vcov.=vcov(object, complete=FALSE)`. (3) The `hccm` method will generally return a matrix of full rank even if the model has aliased terms. Similarly `vcov.=vcov(Boot(object))` may return a full rank matrix, or it will a matrix with NA corresponding to aliased regressors if same regressors are aliased in every bootstrap sample.
`...`	arguments to pass down.

Value

Invisibly returns object for a data object, or summary for a model object.

Note

The method brief.matrix calls brief.data.frame.

Author(s)

John Fox jfox@mcmaster.ca

References

Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.

Examples

brief(rnorm(100))
brief(Duncan)
brief(OBrienKaiser, elided=TRUE)
brief(matrix(1:500, 10, 50))
brief(lm)

mod.prestige <- lm(prestige ~ education + income + type, Prestige)
brief(mod.prestige, pvalues=TRUE)
brief(mod.prestige, ~ type)
mod.mroz <- glm(lfp ~ ., data=Mroz, family=binomial)
brief(mod.mroz)

car

Companion to Applied Regression

v3.0-10

GPL (>= 2)

Authors

John Fox [aut, cre], Sanford Weisberg [aut], Brad Price [aut], Daniel Adler [ctb], Douglas Bates [ctb], Gabriel Baud-Bovy [ctb], Ben Bolker [ctb], Steve Ellison [ctb], David Firth [ctb], Michael Friendly [ctb], Gregor Gorjanc [ctb], Spencer Graves [ctb], Richard Heiberger [ctb], Pavel Krivitsky [ctb], Rafael Laboissiere [ctb], Martin Maechler [ctb], Georges Monette [ctb], Duncan Murdoch [ctb], Henric Nilsson [ctb], Derek Ogle [ctb], Brian Ripley [ctb], William Venables [ctb], Steve Walker [ctb], David Winsemius [ctb], Achim Zeileis [ctb], R-Core [ctb]

Initial release

2020-09-23