robust

A fitted model of any class that is supported by the <code>vcov*()</code>-functions
from the sandwich package. For <code>svy()</code>, <code>x</code> must be
<code>lm</code> object, fitted with weights.

String, indicating the name of the <code>vcov*()</code>-function
from the sandwich-package, e.g. <code>vcov.fun = "vcovCL"</code>.

vcov.fun

Character vector, specifying the estimation type for the
robust covariance matrix estimation (see <code><a rd-options="sandwich" href="/link/vcovHC?package=sjstats&version=0.17.5&to=sandwich" data-mini-rdoc="sandwich::vcovHC">vcovHC</a></code>
for details).

vcov.type

List of named vectors, used as additional arguments that
are passed down to <code>vcov.fun</code>.

vcov.args

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

<code>robust()</code> computes robust standard error for regression models.
 This method calls one of the <code>vcov*()</code>-functions from the
 sandwich-package for robust covariance matrix estimators. Results are
 returned as tidy data frame.<code>svy()</code> is intended to compute standard errors for survey
 designs (complex samples) fitted with regular <code>lm</code> or
 <code>glm</code> functions, as alternative to the survey-package.
 It simulates sampling weights by adjusting the residual degrees
 of freedom based on the precision weights used to fit <code>x</code>,
 and then calls <code>robust()</code> with the adjusted model.

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' and other model objects).
The focus of most functions lies on summary statistics or fit
measures for regression models, including generalized linear
models, mixed effects models and Bayesian 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

Daniel L<c3><bc>decke

robust function

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

robust: Robust standard errors for regression models

Description

Usage

Arguments

Value

Examples