Print data objects and statistical model summaries in abbreviated form.
brief(object, ...)# S3 method for 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="" matrix="" brief(object,="" rows="if" (nr="" <="10)" ...)<="" p="">
# S3 method for numeric
brief(object, rows = c(2, 1), elided = TRUE, ...)
# S3 method for integer
brief(object, rows = c(2, 1), elided = TRUE, ...)
# S3 method for character
brief(object, rows = c(2, 1), elided = TRUE, ...)
# S3 method for factor
brief(object, rows=c(2, 1), elided=TRUE, ...)
# S3 method for list
brief(object, rows = c(2, 1), elided = TRUE, ...)
# S3 method for function
brief(object, rows = c(5, 3), elided = TRUE, ...)
# S3 method for lm
brief(object, terms = ~ .,
intercept=missing(terms), pvalues=FALSE,
digits=3, horizontal=TRUE, vcov., ...)
# S3 method for glm
brief(object, terms = ~ .,
intercept=missing(terms), pvalues=FALSE,
digits=3, horizontal=TRUE, vcov., dispersion, exponentiate, ...)
# S3 method for multinom
brief(object, terms = ~ .,
intercept=missing(terms), pvalues=FALSE,
digits=3, horizontal=TRUE, exponentiate=TRUE, ...)
# S3 method for polr
brief(object, terms = ~ .,
intercept, pvalues=FALSE,
digits=3, horizontal=TRUE, exponentiate=TRUE, ...)
# S3 method for default
brief(object, terms = ~ .,
intercept=missing(terms), pvalues=FALSE,
digits=3, horizontal=TRUE, ...)
=>
a data or model object to abbreviate.
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.
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.
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).
controls whether to report the number of elided elements, rows, or columns; default is TRUE
.
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.
a one-sided formula giving the terms to summarize; the default is ~ .
---i.e., to summarize all terms in the model.
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.
include the p-value for each coefficient in the table; default is FALSE
.
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.
significant digits for printing.
if TRUE
(the default), orient the summary produced by brief
horizontally, which typically saves space.
see summary.glm
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.
Invisibly returns object
for a data object, or summary for a model object.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
# NOT RUN {
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)
# }
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