preprocess2

An object of class lm, fixest or felm

object

A vector with the names of the clusters

cluster

A character scalar - fixed effect to be projected out, or NULL

The univariate coefficients for which a hypothesis is to be tested

param

bootcluster

Logical. If TRUE, <code>boottest()</code> omits rows with missing variables that are added to the model via the <code>cluster</code> argument in <code>boottest()</code>

na_omit

function that pre-processes regression objects of type lm, fixest and feols

Implementation of the fast algorithm for wild cluster bootstrap
inference developed in Roodman et al (2019, STATA Journal) for
linear regression models
<https://journals.sagepub.com/doi/full/10.1177/1536867X19830877>,
which makes it feasible to quickly calculate bootstrap test
statistics based on a large number of bootstrap draws even for
large samples - as long as the number of bootstrapping clusters
is not too large. Multiway clustering, regression weights,
bootstrap weights, fixed effects and subcluster bootstrapping
are supported. Further, both restricted (WCR) and unrestricted
(WCU) bootstrap are supported. Methods are provided for a variety
of fitted models, including 'lm()', 'feols()'
(from package 'fixest') and 'felm()' (from package 'lfe').

preprocess2: function that pre-processes regression objects of type lm, fixest and feols

Description

Usage

Arguments

Value