| Name : R-esvis
| |
| Version : 0.3.1
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.31.2
| Date : 2024-06-14 12:09:51
|
| Group : Development/Libraries/Other
| Source RPM : R-esvis-0.3.1-lp153.31.2.src.rpm
|
| Size : 1.18 MB
| |
| Packager : (none)
| |
| Summary : Visualization and Estimation of Effect Sizes
|
Description :
A variety of methods are provided to estimate and visualize
distributional differences in terms of effect sizes. Particular
emphasis is upon evaluating differences between two or more
distributions across the entire scale, rather than at a single point
(e.g., differences in means). For example, Probability-Probability (PP)
plots display the difference between two or more distributions, matched
by their empirical CDFs (see Ho and Reardon, 2012;
< doi:10.3102/1076998611411918>), allowing for examinations of where on
the scale distributional differences are largest or smallest. The area
under the PP curve (AUC) is an effect-size metric, corresponding to the
probability that a randomly selected observation from the x-axis
distribution will have a higher value than a randomly selected
observation from the y-axis distribution. Binned effect size plots are
also available, in which the distributions are split into bins (set by
the user) and separate effect sizes (Cohen\'s d) are produced for each
bin - again providing a means to evaluate the consistency (or lack
thereof) of the difference between two or more distributions at
different points on the scale. Evaluation of empirical CDFs is also
provided, with built-in arguments for providing annotations to help
evaluate distributional differences at specific points (e.g.,
semi-transparent shading). All function take a consistent argument
structure. Calculation of specific effect sizes is also possible. The
following effect sizes are estimable: (a) Cohen\'s d, (b) Hedges\' g, (c)
percentage above a cut, (d) transformed (normalized) percentage above a
cut, (e) area under the PP curve, and (f) the V statistic (see Ho,
2009; < doi:10.3102/1076998609332755>), which essentially transforms the
area under the curve to standard deviation units. By default, effect
sizes are calculated for all possible pairwise comparisons, but a
reference group (distribution) can be specified.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
