summary.felm | R Documentation |
summary
method for class "felm"
.
## S3 method for class 'felm'
summary(
object,
...,
robust = !is.null(object$clustervar) || getOption("lfe.robust"),
lhs = NULL
)
object |
an object of class |
... |
further arguments passed to or from other methods. |
robust |
logical. Use robust standard errors. See notes. |
lhs |
character. If multiple left hand sides, specify the name of the one to obtain a summary for. |
The function summary.felm
returns an object of class
"summary.felm"
. It is quite similar to en "summary.lm"
object, but not entirely compatible.
The "summary.felm"
object is a list containing the following fields:
residuals |
a numerical vector. The residuals of the full system, with dummies. |
p |
an integer. The total number of coefficients, including those projected out. |
Pp |
an integer. The number of coefficients, excluding those projected out. |
coefficients |
a Pp x 4 matrix with columns for the estimated coefficients, their standard errors, t-statistic and corresponding (two-sided) p-value. |
rse |
residual standard error. |
r2 |
R^2, the fraction of variance explained by the model. |
r2adj |
Adjusted R^2. |
fstat |
F-statistic. |
pval |
P-values. |
P.fstat |
Projected F-statistic. The result of a
call to |
fe |
list of factors. A list of the terms in the second part of the model. |
lhs. |
character. If
|
iv1fstat |
F-statistic for excluded instruments in 1. step IV, see
|
iv1pval |
P-value for |
The standard errors are adjusted for the reduced degrees of freedom coming from the dummies which are implicitly present. They are also small-sample corrected.
If the robust
parameter is FALSE
, the returned object will
contain ordinary standard errors. If the robust
parameter is
TRUE
, clustered standard errors are reported if a cluster was
specified in the call to felm
; if not, heteroskedastic robust
standard errors are reported.
Several F-statistics reported. The P.fstat
is for the projected
system. I.e. a joint test on whether all the Pp
coefficients in
coefficients
are zero. Then there are fstat
and pval
which is a test on all the coefficients including the ones projected out,
except for an intercept. This statistic assumes i.i.d. errors and is not
reliable for robust or clustered data.
For a 1st stage IV-regression, an F-statistic against the model with excluded instruments is also computed.
waldtest()
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