Obtain various statistics from an estimation
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.
coeftable(object, vcov = NULL, ssc = NULL, cluster, keep, drop, order, ...) pvalue(object, vcov, ssc, cluster, keep, drop, order, ...) tstat(object, vcov, ssc, cluster, keep, drop, order, ...) se(object, vcov, ssc, cluster, keep, drop, order, ...)
object |
An estimation. For example obtained from |
vcov |
Versatile argument to specify the VCOV. In general, it is either a character scalar equal to a VCOV type, either a formula of the form: |
ssc |
An object of class |
cluster |
[Fixest specific.] 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 |
... |
Other arguments to be passed to |
se |
[Fixest specific.] Character scalar. Which kind of standard error should be computed: “iid”, “hetero”, “cluster”, “twoway”, “threeway” or “fourway”? By default if there are fixed-effects in the estimation: |
This set of functions is primarily constructed for fixest
estimations. Although it can work for non-fixest
estimations, support for exotic estimation procedures that do not report standardized coefficient tables is highly limited.
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.
pvalue
: Extracts the p-value of an estimation
tstat
: Extracts the t-statistics of an estimation
se
: Extracts the standard-error 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")
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