Optional, unquoted names of variables that should be selected for
further processing. Required, if <code>x</code> is a data frame (and no vector)
and only selected variables from <code>x</code> should be processed. You may also
use functions like <code>:</code> or tidyselect's <code><a rd-options="tidyselect" href="/link/select_helpers?package=sjstats&version=0.17.4&to=tidyselect" data-mini-rdoc="tidyselect::select_helpers">select_helpers</a></code>.

<code>gmd()</code> computes Gini's mean difference for a numeric vector
 or for all numeric vectors in a 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' 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

gmd function

Optional, unquoted names of variables that should be selected for
further processing. Required, if <code>x</code> is a data frame (and no vector)
and only selected variables from <code>x</code> should be processed. You may also
use functions like <code>:</code> or tidyselect's <code><a rd-options='tidyselect' href='select_helpers'>select_helpers</a></code>.

gmd: Gini's Mean Difference

Description

Usage

Arguments

Value

References

Examples