Merge branch 'release/2.5.4'

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: supernova
 Title: Judd, McClelland, & Ryan Formatting for ANOVA Output
-Version: 2.5.3
-Date: 2022-07-11
+Version: 2.5.4
+Date: 2022-07-28
 Authors@R: c(
     person("Adam", "Blake", , "[email protected]", role = c("cre", "aut"),
            comment = c(ORCID = "0000-0001-7881-8652")),

NEWS.md

@@ -1,53 +1,49 @@
-# supernova 2.5.3
+# supernova 2.5.4
+
+- Fix print error where `generate_models()` would only print the comparison models for type III SS.
 
-* 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.
+# supernova 2.5.3
 
+- 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.
 
 # supernova 2.5.2
 
 ## Breaking (kind of)
 
-* Deprecate `superanova()` as it was just an alias to `supernova()` (which was confusing for some students)
-
+- Deprecate `superanova()` as it was just an alias to `supernova()` (which was confusing for some students)
 
 # supernova 2.5.1
 
-* Fix issue where models with long calls (i.e. `deparse(model$call)` results in a vector of length greater than 1) would break the functionality of `listwise_delete()`
-* Change print method for `generate_models()` to look clean and comprehensible in Jupyter Notebooks.
-
+- Fix issue where models with long calls (i.e. `deparse(model$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.
 
 # supernova 2.5.0
 
-* 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
+- 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`](https://github.com/UCLATALL/coursekata-r).
-* **Breaking**: drop support for R 3.4
-
+- Fix printing in RMarkdown documents where `supernova()` output was interpreted as a table.
+- Move `estimate-extraction` functions to [`coursekata`](https://github.com/UCLATALL/coursekata-r).
+- **Breaking**: drop support for R 3.4
 
 # supernova 2.4.4
 
-* Remove `supernova-vctrs` from exports
-
+- Remove `supernova-vctrs` from exports
 
 # supernova 2.4.3
 
-* Fix issues with `lintr` causing `R CMD CHECK` to fail
-* Change maintainer to [@adamblake](https://github.com/adamblake)
-* Change mislabeled factor level in `Fingers$Interest` to "Very Interested"
-
+- Fix issues with `lintr` causing `R CMD CHECK` to fail
+- Change maintainer to [@adamblake](https://github.com/adamblake)
+- Change mislabeled factor level in `Fingers$Interest` to "Very Interested"
 
 # supernova 2.4.2
 
-* Ensure appropriate version of `pillar` is available (thanks @cedricbatailler)
-
+- Ensure appropriate version of `pillar` is available (thanks @cedricbatailler)
 
 # supernova 2.4.1
 
-* Small tweaks to make the package work on R 3.4.0
-
+- Small tweaks to make the package work on R 3.4.0
 
 # supernova 2.4.0
 
@@ -62,69 +58,62 @@ There are four new pairwise comparisons functions:
 
 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.
 
-
 # supernova 2.3.0
 
-* 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](https://github.com/ave-63)!)
-
+- 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](https://github.com/ave-63)!)
 
 # supernova 2.2.3
 
-* Remove dependency on `dplyr` because it changes too quickly and has too many other dependencies
-* Mild refactoring to improve code readability
-
+- Remove dependency on `dplyr` because it changes too quickly and has too many other dependencies
+- Mild refactoring to improve code readability
 
 # supernova 2.2.2
 
-* Patch to keep up with changes to `lme4`
-
+- Patch to keep up with changes to `lme4`
 
 # supernova 2.2.1
 
-* Add support for mixed models (as in nested and crossed). See the README for more information.
-
+- Add support for mixed models (as in nested and crossed). See the README for more information.
 
 # supernova 2.2.0
 
 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
+- 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
-
+- Refactor utility functions into utils.R
+- Add internal documentation for utility functions
 
 # supernova 2.1.1
 
-* Added a `NEWS.md` file to track changes to the package.
+- Added a `NEWS.md` file to track changes to the package.
 
-* Created and added a logo to the package. (#21, @adamblake)
+- 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 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)
+- 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()`
+- 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.
+- 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.
 
-
 # supernova 2.0.0
 
-* Added support for multiple regression using Type III sums of squares
+- 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).
+- 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).
 
 # supernova 1.1.0
 
-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.
+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.

R/generate_models.R

@@ -258,7 +258,7 @@ drop_term <- function(fit, term) {
 #' @export
 print.comparison_models <- function(x, ...) {
   full_model <- attr(x, "model")
-  x <- generate_models.formula(as.formula(full_model))
+  x <- generate_models.formula(as.formula(full_model), attr(x, "type"))
 
   if (vctrs::vec_is_empty(x)) {
     cli::cli_alert("No comparisons for empty model.")

R/supernova.R

@@ -379,8 +379,9 @@ print.supernova <- function(x, pcut = 4, ...) {
   tbl <- lapply(tbl, function(x) gsub("\\s*NA\\s*", "   ", x)) %>%
     as.data.frame(stringsAsFactors = FALSE)
 
-  # trim leading 0 from p
+  # trim leading 0 from p and PRE
   tbl[["p"]] <- substring(tbl[["p"]], 2)
+  tbl[["PRE"]] <- substring(tbl[["PRE"]], 2)
 
   # TABLE FORMATTING
   # add placeholders for null model

cran-comments.md

@@ -1,25 +1,23 @@
 ## Release summary
 
-* 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.
+- Fix print error where `generate_models()` would only print the comparison models for type III SS.
 
 ## Test environments
 
-- Local install on macOS Monterey 12.4 (ARM); R 4.2.1
+- Local install on macOS Monterey 12.5 (ARM); R 4.2.1
 - GitHub Actions
-  * macOS, 11.6.6; R 4.2.1
-  * Microsoft Windows Server 2022, 10.0.20348; R 4.2.1
-  * Ubuntu, 20.04; R-devel, R 4.2.1
-
+  - macOS, 11.6.8; R 4.2.1
+  - Microsoft Windows Server 2022, 10.0.20348; R 4.2.1
+  - Ubuntu, 20.04.4; R-devel, R 4.2.1
+  - `check_rhub()`
+  - `check_win_devel()`
 
 ## R CMD check results
 
 0 errors v | 0 warnings v | 0 notes v
 
 R CMD check succeeded
 
-
 ## Reverse dependencies
 
 No known reverse dependencies (no results from `devtools::revdep('supernova')`)

tests/testthat/_snaps/generate_models.md

@@ -4,35 +4,35 @@
       generate_models(test_formula, type = 1)
     Output
       
-      -- Comparison Models for Type III SS -------------------------------------------
+      -- Comparison Models for Type I SS ---------------------------------------------
       
       -- Full Model
       complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
       simple:  y ~ NULL
       
       -- a
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~     b + c + a:b + a:c + b:c + a:b:c
+      complex: y ~ a
+      simple:  y ~ NULL
       
       -- b
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a +     c + a:b + a:c + b:c + a:b:c
+      complex: y ~ a + b
+      simple:  y ~ a
       
       -- c
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a + b +     a:b + a:c + b:c + a:b:c
+      complex: y ~ a + b + c
+      simple:  y ~ a + b
       
       -- a:b
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a + b + c +       a:c + b:c + a:b:c
+      complex: y ~ a + b + c + a:b
+      simple:  y ~ a + b + c
       
       -- a:c
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a + b + c + a:b +       b:c + a:b:c
+      complex: y ~ a + b + c + a:b + a:c
+      simple:  y ~ a + b + c + a:b
       
       -- b:c
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a + b + c + a:b + a:c +       a:b:c
+      complex: y ~ a + b + c + a:b + a:c + b:c
+      simple:  y ~ a + b + c + a:b + a:c
       
       -- a:b:c
       complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
@@ -45,35 +45,35 @@
       generate_models(test_formula, type = 2)
     Output
       
-      -- Comparison Models for Type III SS -------------------------------------------
+      -- Comparison Models for Type II SS --------------------------------------------
       
       -- Full Model
       complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
       simple:  y ~ NULL
       
       -- a
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~     b + c + a:b + a:c + b:c + a:b:c
+      complex: y ~ a + b + c +             b:c
+      simple:  y ~     b + c +             b:c
       
       -- b
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a +     c + a:b + a:c + b:c + a:b:c
+      complex: y ~ a + b + c +       a:c
+      simple:  y ~ a +     c +       a:c
       
       -- c
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a + b +     a:b + a:c + b:c + a:b:c
+      complex: y ~ a + b + c + a:b
+      simple:  y ~ a + b +     a:b
       
       -- a:b
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a + b + c +       a:c + b:c + a:b:c
+      complex: y ~ a + b + c + a:b + a:c + b:c
+      simple:  y ~ a + b + c +       a:c + b:c
       
       -- a:c
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a + b + c + a:b +       b:c + a:b:c
+      complex: y ~ a + b + c + a:b + a:c + b:c
+      simple:  y ~ a + b + c + a:b +       b:c
       
       -- b:c
-      complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
-      simple:  y ~ a + b + c + a:b + a:c +       a:b:c
+      complex: y ~ a + b + c + a:b + a:c + b:c
+      simple:  y ~ a + b + c + a:b + a:c
       
       -- a:b:c
       complex: y ~ a + b + c + a:b + a:c + b:c + a:b:c
@@ -127,19 +127,19 @@
       generate_models(test_lm, type = 1)
     Output
       
-      -- Comparison Models for Type III SS -------------------------------------------
+      -- Comparison Models for Type I SS ---------------------------------------------
       
       -- Full Model
       complex: mpg ~ hp + disp + hp:disp
       simple:  mpg ~ NULL
       
       -- hp
-      complex: mpg ~ hp + disp + hp:disp
-      simple:  mpg ~      disp + hp:disp
+      complex: mpg ~ hp
+      simple:  mpg ~ NULL
       
       -- disp
-      complex: mpg ~ hp + disp + hp:disp
-      simple:  mpg ~ hp +        hp:disp
+      complex: mpg ~ hp + disp
+      simple:  mpg ~ hp
       
       -- hp:disp
       complex: mpg ~ hp + disp + hp:disp
@@ -152,19 +152,19 @@
       generate_models(test_lm, type = 2)
     Output
       
-      -- Comparison Models for Type III SS -------------------------------------------
+      -- Comparison Models for Type II SS --------------------------------------------
       
       -- Full Model
       complex: mpg ~ hp + disp + hp:disp
       simple:  mpg ~ NULL
       
       -- hp
-      complex: mpg ~ hp + disp + hp:disp
-      simple:  mpg ~      disp + hp:disp
+      complex: mpg ~ hp + disp
+      simple:  mpg ~      disp
       
       -- disp
-      complex: mpg ~ hp + disp + hp:disp
-      simple:  mpg ~ hp +        hp:disp
+      complex: mpg ~ hp + disp
+      simple:  mpg ~ hp
       
       -- hp:disp
       complex: mpg ~ hp + disp + hp:disp