summary.lm {stats}  R Documentation 
summary
method for class "lm"
.
## S3 method for class 'lm'
summary(object, correlation = FALSE, symbolic.cor = FALSE, ...)
## S3 method for class 'summary.lm'
print(x, digits = max(3, getOption("digits")  3),
symbolic.cor = x$symbolic.cor,
signif.stars = getOption("show.signif.stars"), ...)
object 
an object of class 
x 
an object of class 
correlation 
logical; if 
digits 
the number of significant digits to use when printing. 
symbolic.cor 
logical. If 
signif.stars 
logical. If 
... 
further arguments passed to or from other methods. 
print.summary.lm
tries to be smart about formatting the
coefficients, standard errors, etc. and additionally gives
‘significance stars’ if signif.stars
is TRUE
.
Aliased coefficients are omitted in the returned object but restored
by the print
method.
Correlations are printed to two decimal places (or symbolically): to
see the actual correlations print summary(object)$correlation
directly.
The function summary.lm
computes and returns a list of summary
statistics of the fitted linear model given in object
, using
the components (list elements) "call"
and "terms"
from its argument, plus
residuals 
the weighted residuals, the usual residuals
rescaled by the square root of the weights specified in the call to

coefficients 
a 
aliased 
named logical vector showing if the original coefficients are aliased. 
sigma 
the square root of the estimated variance of the random error
where 
df 
degrees of freedom, a 3vector 
fstatistic 
(for models including nonintercept terms) a 3vector with the value of the Fstatistic with its numerator and denominator degrees of freedom. 
r.squared 
where 
adj.r.squared 
the above 
cov.unscaled 
a 
correlation 
the correlation matrix corresponding to the above

symbolic.cor 
(only if 
na.action 
from 
The model fitting function lm
, summary
.
Function coef
will extract the matrix of coefficients
with standard errors, tstatistics and pvalues.
## Continuing the lm(.) example:
coef(lm.D90) # the bare coefficients
sld90 < summary(lm.D90 < lm(weight ~ group 1)) # omitting intercept
sld90
coef(sld90) # much more
## model with *aliased* coefficient:
lm.D9. < lm(weight ~ group + I(group != "Ctl"))
Sm.D9. < summary(lm.D9.)
Sm.D9. # shows the NA NA NA NA line
stopifnot(length(cc < coef(lm.D9.)) == 3, is.na(cc[3]),
dim(coef(Sm.D9.)) == c(2,4), Sm.D9.$df == c(2, 18, 3))