File: conf_int.Rd

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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/conf_int.R
\name{conf_int}
\alias{conf_int}
\title{Calculate confidence intervals for all or selected regression coefficients in a fitted model}
\usage{
conf_int(obj, vcov, level = 0.95, test = "Satterthwaite", coefs = "All", ...)
}
\arguments{
\item{obj}{Fitted model for which to calculate confidence intervals.}

\item{vcov}{Variance covariance matrix estimated using \code{vcovCR} or a
character string specifying which small-sample adjustment should be used to
calculate the variance-covariance.}

\item{level}{Desired coverage level for confidence intervals.}

\item{test}{Character vector specifying which small-sample corrections to
calculate. \code{"z"} returns a z test (i.e., using a standard normal
reference distribution). \code{"naive-t"} returns a t test with \code{m -
1} degrees of freedom. \code{"Satterthwaite"} returns a Satterthwaite
correction. \code{"saddlepoint"} returns a saddlepoint correction. Default
is \code{"Satterthwaite"}.}

\item{coefs}{Character, integer, or logical vector specifying which
coefficients should be tested. The default value \code{"All"} will test all
estimated coefficients.}

\item{...}{Further arguments passed to \code{\link{vcovCR}}, which are only
needed if \code{vcov} is a character string.}
}
\value{
A data frame containing estimated regression coefficients, standard errors, and confidence intervals.
}
\description{
\code{conf_int} reports confidence intervals for each coefficient estimate in a fitted
linear regression model, using a sandwich estimator for the standard errors
and a small sample correction for the critical values. The small-sample correction is
based on a Satterthwaite approximation.
}
\examples{
data("Produc", package = "plm")
lm_individual <- lm(log(gsp) ~ 0 + state + log(pcap) + log(pc) + log(emp) + unemp, data = Produc)
individual_index <- !grepl("state", names(coef(lm_individual)))
conf_int(lm_individual, vcov = "CR2", cluster = Produc$state, coefs = individual_index)

V_CR2 <- vcovCR(lm_individual, cluster = Produc$state, type = "CR2")
conf_int(lm_individual, vcov = V_CR2, level = .99, coefs = individual_index)

}
\seealso{
\code{\link{vcovCR}}
}