The correlation() function was added. This function
returns the correlation or association statistics for different types of
variables in a data frame.
Updates to documentation.
pairwiseNominalIndependence() function to allow for not
using Yates’ correction in 2 x 2 chi-square test.A fix was applied to the transformTukey() function
to allow for samples sizes greater than 5000.
A fix was applied to the cramerV() function to not
round the value for the total sample size.
A fix was applied to the cramerV() function to avoid
an error in the case of certain sparse matrices.
An update was made in the example for
wilcoxonPairedR() to reflect the handling of paired samples
in wilcox.test(). Specifically, this is in reference to PR
14359, the correction for which doesn’t allow paired arguments for
formula input for the t.test() and
wilcox.test() functions.
URLs in the documentation were updated to https where appropriate.
MASS::rlm models were added to the accuracy() function.
The ephronRSquared() function now accepts model objects.
The accuracy(), ephronRSquared(), and nagelkerke() functions now accept glmmTMB model objects.
The wilcoxonOneSampleR() and
wilcoxonPairedR() functions were modified to adjust the
sample size for tied values.
Two functions, mangiaficoD() and
multiMangiaficoD() were added. These functions calculate
the difference in medians for two groups divided by pooled median
absolute deviation. This is somewhat analogous to a nonparametric
version of Cohen’s d.
pairwiseNominalIndependence() function was modified
to include chi-square, G, and df values in the output.The scheirerRayHare() function was modified to
include an option to use type-II sum-of-squares.
The cliffDelta() function has been modified to
better handle large sample sizes.
The cateNelsonFixedY() function was added. This
conducts a Cate-Nelson analysis on bivariate data where the critical Y
value is fixed. This kind of analysis is useful in agronomy studies (for
example, when a 95% yield is of interest), and for other bivariate data
which don’t conform well to linear, curvilinear, or plateau
models.
The cldList() function was revised so that it
returns a data frame with the same letter for all groups when there are
no significant differences, rather than stop and report “no
differences”.
The accuracy() function was revised to include
median absolute error.
As a side note, all mentions of “sex” as demographic variables in the package were changed to “gender”. The same change is being made on https://rcompanion.org/handbook/ .
The efronRSquared() function was added. It produces
Efron’s pseudo R-squared from vectors of actual y values, residuals, and
predicted values. It can also produce MAE, MAPE, MSE, RMSE, and CV. The
accuracy() function also produces these statistics directly
from a model object.
The countRSquare() function was added. It produces
the count pseudo r-squared for logistic regression or other models with
a binary outcome. This statistic is the number of correctly predicted
outcomes divided by the total number of outcomes.
The oneSampleDominance() function was added. It
produces a dominance statistic for the one sample case. It can be used
as an effect size statistic for the one-sample sign test, and can be
used with truly ordinal data.
The pairedSampleDominance() function was added. This
is similar to the oneSampleDominance() statistic, but used
in the case of two-sample paired data.
No longer suggests FSA package.
The groupwiseMean() function was updated to allow
for trimmed means, including determining confidence intervals by
bootstrap, and to more formally handle NA values.
The nominalSymmetryTest() function was
improved.
Documentation was updated for the groupwiseHuber()
function.
Two new functions were added that calculate effect sizes for the
two-sample case, such as might be used with a Wilcoxon-Mann-Whitney
test. These are wilcoxonPS(), that calculates Grissom and
Kim’s probability of superiority, and wilcoxonOR(), that
calculates Agresti’s generalized odds ratio.
These functions complement others that could be used as effect
size statistics in the two-sample case. vda() for Vargha
and Delaney’s A, cliffDelta() for Cliff’s delta,
wilcoxonRG() for Glass rank biserial correlation
coefficient, and wilcoxonR() for the r statistic
Z/sqrt(N).
Minor bug fix in freemanTheta() function.
Minor bug fixes, particularly with the
groupwiseCMH() function to prevent an error in some
cases.
quantileCI(), that calculates the
confidence interval for the median of a numeric or ordered factor
variable, based on a method included in Conover, Practical Nonparametric
Statistics, 3rd.A function was added, blom(), which calculates
normal scores transformation by Blom, van der Waerden, Tukey, and rankit
methods, as well as z-score transformation, and rescaling to a specified
range.
A function was added, ordinalEtaSquared(), that
calculates eta-squared as an effect size statistic, following a
Kruskal-Wallis test, or for a table with one ordinal variable and one
nominal variable; confidence intervals by bootstrap.
A function was added, wilcoxonRG(), that calculates
the Glass rank biserial correlation coefficient effect size for
Mann-Whitney two-sample rank-sum test; confidence intervals by
bootstrap.
A function was added, wilcoxonPairedRC(), that
calculates the paired-samples rank biserial correlation coefficient
effect size for paired Wilcoxon signed-rank test; confidence intervals
by bootstrap.
A function was added, wilcoxonOneSampleRC(), that
calculates the paired-samples rank biserial correlation coefficient
effect size for one sample Wilcoxon signed-rank test; confidence
intervals by bootstrap
A modification was made to some effect size functions so that
they will not fail when there are instances of the calculation of the
statistic failing during the bootstrap procedure. In these cases, the
confidence interval is reported as NA (the default) or as the confidence
interval based on the successful calculations.
(epsilonSquared(), vda(),
cliffDelta(), wilcoxonR(),
spearmanRho(), phi(), CramerV(),
CramerVFit(), cohenW(), cohenG(),
freemanTheta().
A small modification was made to compareGLM() and
compareLM() so that models with a long formula won’t cause
an error and the function to fail.
The function multiVDA() was modified to include the
Glass rank biserial correlation coefficient.
The function phi() was added to calculate the effect
size for a 2 x 2 table of counts, and to optionally produce a confidence
interval.
The function cohenW() was updated to optionally
produce a confidence interval.
The function wilcoxonZ() was added. It extracts the
Z statistic from a two-sample, paired, and one-sample Wilcoxon
tests.
The wilcoxonR(), wilcoxonPairedR(), and
wilcoxonOneSampleR() functions were updated to produce
confidence intervals more quickly.
kendallW() and spearmanRho().Confidence intervals by bootstrap for some effect size statistics
were added, specifically for Cohen’s g, odds ratio, Cohen’s P. The
relevant function is: cohenG().
A function was added to calculate the maximum Vargha and
Delaney’s A or Cliff’s delta as an effect size for Kruskal-Wallis test.
multiVDA().
vda() and
cliffDelta().Confidence intervals by bootstrap for some effect size statistics
were added, specifically for r for Wilcoxon tests, Cramer’s V,
epsilon-squared, and Freeman’s theta. The relevant functions are:
wilcoxonR(), wilcoxonPairedR(),
wilcoxonOneSampleR(), epsilonSquared(),
freemanTheta(), cramerV(),
cramerVFit().
The accuracy function was updated to include output for the coefficient of variation for models.
Some functions were removed that conducted pairwise post-hoc
tests where better methods exist: pairwiseSignTest(),
pairwiseSignMatrix().
The pairwiseMcnemar() function was updated to
include statistics (chi-square, Z) in output.
The transformTukey() function was modified to allow
the user to suppress screen output, and an option was added to return
the value of lambda rather than the transformed data.
The nagelkerke() function was updated to allow the
new lmerModLmerTest objects
nagelkerkeHermite(), pairwiseDifferences(),
pairwiseOrdinalMatrix(),
pairwiseOrdinalPairedMatrix(),
pairwiseOrdinalPairedTest(),
pairwiseOrdinalTest(), pairwiseRobustMatrix(),
pairwiseRobustTest().multiVDA(),
Calculates Vargha and Delaney’s A and Cliff’s delta pairwise across
groups.Functions have been amended or added:
cohenG() - Calculates Cohen’s g and odds ratio for
paired contingency tables, such as those that might be analyzed with
McNemar or McNemar-Bowker tests.cohenH() - Cohen’s h is an effect size to compare two
proportions.wilcoxonR() - Calculates r effect size for
Mann-Whitney, two-sample rank-sum test, or a table with an ordinal
variable and a nominal variable with two levels.wilcoxonOneSampleR() - Calculates r effect size for a
Wilcoxon one-sample signed-rank test.wilcoxonPairedR() - Calculates r effect size for a
Wilcoxon two-sample paired signed-rank test.cohenH() - function to calculate Cohen’s h effect size
for tables.Functions added:
wilcoxonR() - function to calculate r effect size
for Wilcoxon Mann-Whitney rank sum test
wilcoxonPairedR() - function to calculate r effect
size for Wilcoxon signed rank test
wilcoxonOneSampleR() - to calculate r effect size
for one-sample Wilcoxon signed rank test
Minor improvements to: freemanTheta(),
epsilsonSquared()
Improved cateNelson() and cramerV()
functions.
cramerVFit() for goodness of fit testsaccuracy()
functionfreemanTheta() functionepsilonSquared() functionpercentileTest()
and pairwisePercentileTest() functions.scheirerRayHare() function addedaccuracy() function added for minimum maximum
accuracy, MAPE, RMSE, and NRMSE
cramerV() function added to calculate Cramer’s V for
correlation in tables of nominal variables (contingency tables)
nobs problem in nagelkerke() and
nakgelkeHermite() functions.cldList()This package provides custom functions for working through examples and analyses from “Summary and Analysis of Extension Education Program Evaluation in R” and “An R Companion for the Handbook of Biological Statistics”.
There are several functions which provide summary statistics for
grouped data. These function titles tend to start with
groupwise“. They provide means, medians, geometric means,
and Huber M-estimators for groups, along with confidence intervals by
traditional methods and bootstrap.
Function titles starting with pairwise” conduct pairwise
tests among groups as a post-hoc analysis for omnibus tests. At the time
of writing, these tests are Mood’s median test, sign test (for Friedman
test), permutation test, robust anova, and ordinal regression. The
output is a table of comparisons and p-values, or a matrix of
p-values that can be parsed into a compact letter display.
There are also functions that are useful for comparing models.
accuracy(), compareLM(),
compareGLM(), and pairwiseModelAnova(). These
use goodness-of-fit measures like AIC, BIC, and BICc, or likelihood
ratio tests, or accuracy measures like RMSE and Efron’s pseudo
r-square.
Functions for nominal data include post-hoc tests for
Cochran-Mantel-Haenszel test (groupwiseCMH()), for
McNemar–Bowker (pairwiseMcnemR()), and for tests of
association like Chi-square, Fisher exact, and G-test
(pairwiseNominalIndependence()).
A function close to my heart is cateNelson(), which
performs Cate–Nelson analysis for bivariate data.
Examples and vignettes can be found at https://rcompanion.org/handbook/ and https://rcompanion.org/rcompanion/.