robust

A fitted model of any class that is supported by the <code>coeftest()</code>-function.

Character vector, specifying the estimation type for the
heteroskedasticity-consistent covariance matrix estimation
(see <code><a rd-options="sandwich" href="/link/vcovHC?package=sjstats&version=0.7.1&to=sandwich" data-mini-rdoc="sandwich::vcovHC">vcovHC</a></code> for details).

vcov

Logical, <code>TRUE</code> if confidence intervals based on robust
standard errors should be included.

conf.int

Logical, whether to exponentiate the coefficient estimates
and confidence intervals (typical for logistic regression).

exponentiate


Compute robust standard error for regression models. This method
               wraps the <code><a rd-options="lmtest" href="/link/coeftest?package=sjstats&version=0.7.1&to=lmtest" data-mini-rdoc="lmtest::coeftest">coeftest</a></code>-function with
               robust covariance matrix estimators based on the
               <code><a rd-options="sandwich" href="/link/vcovHC?package=sjstats&version=0.7.1&to=sandwich" data-mini-rdoc="sandwich::vcovHC">vcovHC</a></code>-function, and returns the
               result as tidy data frame.


Collection of convenient functions for common statistical computations,
which are not directly provided by R's base or stats packages.
This package aims at providing, first, shortcuts for statistical
measures, which otherwise could only be calculated with additional
effort (like standard errors or root mean squared errors). Second,
these shortcut functions are generic (if appropriate), and can be
applied not only to vectors, but also to other objects as well
(e.g., the Coefficient of Variation can be computed for vectors,
linear models, or linear mixed models; the r2()-function returns
the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects).
The focus of most functions lies on summary statistics or fit
measures for regression models, including generalized linear
models and mixed effects models. However, some of the functions
also deal with other statistical measures, like Cronbach's Alpha,
Cramer's V, Phi etc.

Daniel Lüdecke

sjstats

Collection of Convenient Functions for Common Statistical
Computations

robust function

Character vector, specifying the estimation type for the
heteroskedasticity-consistent covariance matrix estimation
(see <code><a rd-options='sandwich' href='vcovHC'>vcovHC</a></code> for details).


Compute robust standard error for regression models. This method
               wraps the <code><a rd-options='lmtest' href='coeftest'>coeftest</a></code>-function with
               robust covariance matrix estimators based on the
               <code><a rd-options='sandwich' href='vcovHC'>vcovHC</a></code>-function, and returns the
               result as tidy data frame.


robust: Robust standard errors for regression models

Description

Usage

Arguments

Value

Examples