- Remove references to
`Fingers`

data in examples and tests as it may be removed in the near future - Fix issue where using a model fit with an interactive term that has
`factor()`

in it (e.g.`lm(mpg ~ factor(cyl) * hp, data = mtcars)`

) would result in an incorrect*df*(and related values) in the ANOVA table.

- Deprecate
`superanova()`

as it was just an alias to`supernova()`

(which was confusing for some students)

- Fix issue where models with long calls
(i.e.
`deparse(model$call)`

results in a vector of length greater than 1) would break the functionality of`listwise_delete()`

- Change print method for
`generate_models()`

to look clean and comprehensible in Jupyter Notebooks.

- Change the order of the pairs when plotting
`pairwise()`

so that the plot matches the table. - Fix bug where
`pairwise()`

would not recognize categorical variables if they were created by using`factor()`

in the formula, e.g.`pairwise(lm(mpg ~ factor(cyl), data = mtcars))`

. - Fix printing in RMarkdown documents where
`supernova()`

output was interpreted as a table. - Move
`estimate-extraction`

functions to`coursekata`

. **Breaking**: drop support for R 3.4

- Remove
`supernova-vctrs`

from exports

- Fix issues with
`lintr`

causing`R CMD CHECK`

to fail - Change maintainer to @adamblake
- Change mislabeled factor level in
`Fingers$Interest`

to “Very Interested”

- Ensure appropriate version of
`pillar`

is available (thanks @cedricbatailler)

- Small tweaks to make the package work on R 3.4.0

There are four new pairwise comparisons functions:

`pairwise()`

`pairwise_t()`

`pairwise_bonferroni()`

`pairwise_tukey()`

Each of these determines all the pairwise comparisons that can be
made for a model (fit by `lm()`

) and then computes the
comparisons. For `pairwise_t()`

no correction is made for
multiple comparisons, but for the others, the named correction is made.
These corrections can also be specified as arguments to the
`pairwise()`

wrapper function. Each function produces output
that has customized printing, supports most (if not all) normal data
frame actions, and a plotting function that graphs the mean differences
and their confidence intervals.

- Dependency on
`lme4`

is moved to Suggests. Models implementing`lmerMod`

are handled via`supernova.lmerMod`

and`variables.lmerMod`

but use of the`lme4`

package is limited to tests. - More robust and readable implementation of
`variables()`

using the new formula utility functions added. See`?formula_building`

,`?formula_expansion`

, and`?formula_extraction`

. - Add a new function
`equation()`

to extract the fitted equation from a linear model (`lm()`

) (thanks for the suggestion from @ave-63!)

- Remove dependency on
`dplyr`

because it changes too quickly and has too many other dependencies - Mild refactoring to improve code readability

- Patch to keep up with changes to
`lme4`

- Add support for mixed models (as in nested and crossed). See the README for more information.

Extend supernova to handle within (crossed) designs

- Add
`lme4`

and`dplyr`

to Imports - Update R dependency to 3.5.0 (for serialized data; Rds)
- Convert
`supernova`

to S3 class with methods for`lm`

and`lmerMod`

- Add tests for
`supernova()`

for crossed (but not nested)`lmer()`

fits - Extend
`print.supernova`

to handle new models

Minor changes:

- Refactor utility functions into utils.R
- Add internal documentation for utility functions

Added a

`NEWS.md`

file to track changes to the package.Created and added a logo to the package. (#21, @adamblake)

Added the ability to change the type of sums of squares to calculate when computing the ANOVA tables. Users can choose from 1/I/sequential, 2/II/hierarchical, 3/III/orthogonal. (#22, @adamblake)

Added pedagogical function

`generate_models()`

for showing which models are being compared when evaluating terms in a model. This function also supports specification of the type of sums of squares to use. (#22, @adamblake)Updated the README to be generated from an Rmd file and to include information and examples regarding how to calculate different SS types and how to use

`generate_models()`

Added a data frame identical to Servers named Tables. This is a more appropriate name for the dataset because each row describes what happened at a table in the restaurant.

- Updated variable names and documentation to “table” as well.
- Added deprecation notice to Servers documentation as the table will be removed in the future.

Added support for multiple regression using Type III sums of squares

Updated README for more information, examples, and a description of how the calculation of the ANOVA tables follows the model comparison approach used in Judd, McClelland, & Ryan (2017).

This version of supernova is the original distributed on CRAN.
Calculation of supernova() tables with *multiple* predictor
variables in this version will not produce output similar to the
reference text, Judd, McClelland, and Ryan. However, the values for
*single* predictor models are correct.