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".
The function nagelkerke
provides pseudo R-squared values for a variety of model types, as well as
a likelihood ratio test for the model as a whole. An addtional function,
nagelkerkeHermite, is provided for models fit with the
hermite package.
There are several functions that 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 omnibus 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.
compareLM, compareGLM, and
pairwiseModelAnova.
These use goodness-of-fit measures like AIC, BIC, and BICc, or likelihood
ratio tests.
There are a few useful plotting functions, including
plotNormalHistogram that plots a histogram of values and
overlays
a normal curve, and plotPredy which plots of line for predicted
values for a bivariate model. Other plotting functions include producing
density plots.
Functions for nominal data include post-hoc tests for
Cochran-Mantel-Haenszel test (groupwiseCMH),
for McNemar-Bowker test (pairwiseMcnemar),
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.
The functions in this package are used in "Extension Education Program Evaluation in R" which is available at http://rcompanion.org/handbook/ and "An R Companion for the Handbook of Biological Statistics" which is available at http://rcompanion.org/rcompanion/.
The documentation for each function includes an example as well.