coeftable.fixest | R Documentation |
Set of functions to directly extract some commonly used statistics, like the p-value or
the table of coefficients, from estimations. This was first implemented for
fixest
estimations, but has some support for other models.
## S3 method for class 'fixest'
coeftable(
object,
vcov = NULL,
ssc = NULL,
cluster = NULL,
keep = NULL,
drop = NULL,
order = NULL,
list = FALSE,
...
)
## S3 method for class 'fixest'
se(
object,
vcov = NULL,
ssc = NULL,
cluster = NULL,
keep = NULL,
drop = NULL,
order = NULL,
...
)
## S3 method for class 'fixest'
tstat(
object,
vcov = NULL,
ssc = NULL,
cluster = NULL,
keep = NULL,
drop = NULL,
order = NULL,
...
)
## S3 method for class 'fixest'
pvalue(
object,
vcov = NULL,
ssc = NULL,
cluster = NULL,
keep = NULL,
drop = NULL,
order = NULL,
...
)
object |
A |
vcov |
A function to be used to compute the standard-errors of each fixest object. You can
pass extra arguments to this function using the argument |
ssc |
An object of class |
cluster |
Tells how to cluster the standard-errors (if clustering is requested). Can
be either a list of vectors, a character vector of variable names, a formula or an
integer vector. Assume we want to perform 2-way clustering over |
keep |
Character vector. This element is used to display only a subset of variables. This
should be a vector of regular expressions (see |
drop |
Character vector. This element is used if some variables are not to be displayed.
This should be a vector of regular expressions (see |
order |
Character vector. This element is used if the user wants the variables to be
ordered in a certain way. This should be a vector of regular expressions (see |
list |
Logical, default is |
... |
Other arguments to be passed to |
This set of tiny functions is primarily constructed for fixest
estimations.
Returns a table of coefficients, with in rows the variables and four columns: the estimate, the standard-error, the t-statistic and the p-value.
If list = TRUE
then a nested list is returned, the first layer is accessed with
the coefficients names; the second layer with the following values:
coef
, se
, tstat
, pvalue
. For example, with res = coeftable(est, list = TRUE)
you can access the SE of the coefficient x1
with res$x1$se
; and its
coefficient with res$x1$coef
, etc.
se(fixest)
: Extracts the standard-error of an estimation
tstat(fixest)
: Extracts the t-statistics of an estimation
pvalue(fixest)
: Extracts the p-value of an estimation
# Some data and estimation
data(trade)
est = fepois(Euros ~ log(dist_km) | Origin^Product + Year, trade)
#
# Coeftable/se/tstat/pvalue
#
# Default is clustering along Origin^Product
coeftable(est)
se(est)
tstat(est)
pvalue(est)
# Now with two-way clustered standard-errors
# and using coeftable()
coeftable(est, cluster = ~Origin + Product)
se(est, cluster = ~Origin + Product)
pvalue(est, cluster = ~Origin + Product)
tstat(est, cluster = ~Origin + Product)
# Or you can cluster only once:
est_sum = summary(est, cluster = ~Origin + Product)
coeftable(est_sum)
se(est_sum)
tstat(est_sum)
pvalue(est_sum)
# You can use the arguments keep, drop, order
# to rearrange the results
base = iris
names(base) = c("y", "x1", "x2", "x3", "species")
est_iv = feols(y ~ x1 | x2 ~ x3, base)
tstat(est_iv, keep = "x1")
coeftable(est_iv, keep = "x1|Int")
coeftable(est_iv, order = "!Int")
#
# Using lists
#
# Returning the coefficients table as a list can be useful for quick
# reference in markdown documents.
# Note that the "(Intercept)" is renamed into "constant"
res = coeftable(est_iv, list = TRUE)
# coefficient of the constant:
res$constant$coef
# pvalue of x1
res$x1$pvalue
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