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cofad 0.4.0
Analysis and API
- Added participant-level
r scores for within-subjects
and mixed contrasts via within_score = "r". The existing
L score remains the default: use L when
response magnitude matters and r when agreement with the
predicted pattern matters.
- Corrected sums of squares, pooled error variance, and effect sizes
for between-subjects designs with unequal group sizes. Raw and
aggregated input now use the same formulas, and effect-size conversions
preserve contrast direction.
- Corrected the within-only
r_contrast calculation to use
the denominator degrees of freedom from its contrast test. The
paper-ready report now uses the signed r_contrast
consistently and relates its square to the contrast-specific eta-squared
measures.
- Extended competing-contrast support to the app. Favored and rival
weights are standardized before their difference is analyzed, matching
lambda_diff().
- Added conservative
detect_design() suggestions based on
replication, crossing, and nesting. Ambiguous data deliberately fall
back to manual model selection.
calc_contrast_aggregated() no longer requires an
explicit data = NULL.
- Added the corrected mixed-design data set
rosenthal_tbl68_mixed; the historical
rosenthal_tbl68 object remains available for
compatibility.
- Reduced hard dependencies by replacing small uses of
dplyr, Hmisc, lifecycle,
readr, rlang, stringr, and
tibble with base R or foreign. The pipe
remains available for backward compatibility.
Shiny app
- Restored stable, editable table-based model and contrast inputs. The
model table shows automatic design suggestions but always permits manual
changes.
- Added categorized between-subjects, within-subjects, and mixed
examples. Each example loads the model roles and planned weights
documented in its source; examples with published rival hypotheses open
in competing mode.
- Mixed designs now explicitly offer either a between × within
contrast or a within contrast averaged across groups. Pure designs
follow the roles in the model table without redundant activation
controls.
- Added detailed variance-decomposition F tables with ordinary and
partial eta squared, calculation tooltips, directional paper-ready
reports, and interactive Plotly partitions of variation. Mixed output is
explicitly based on participants’ derived within-contrast scores rather
than raw repeated outcomes.
- Reports can be copied as rich HTML with a plain-text fallback. F
tables can be copied as aligned text or HTML and downloaded as
dependency-free DOCX files.
- Added APA 7 citation-copy controls for the tutorial and software
paper. The package-level
citation("cofad") command now
returns both references.
- Improved file validation, example-loading security, small-p-value
formatting, table sizing and alignment, tooltips, collapsible panels,
accessible colors, version display, and responsive copy controls.
Documentation, deployment,
and testing
- Added the 2025 Behavior Research Methods tutorial as the
primary citation, alongside the JOSS software paper.
- Expanded the README with current R, app, Docker, and webR examples;
equations now use GitHub’s native mathematical notation.
- Added a browser-only Shinylive/webR build with automatic GitHub
Pages deployment and a containerized Shiny deployment through
Dockerfile.
- Expanded numerical, validation, design-detection, example-preset,
citation, export, and in-process Shiny server tests. GitHub Actions now
check multiple R versions and platforms and publish test coverage.
- Verified the publication year and DOI metadata for Rosenthal,
Rosnow, and Rubin (2000) and clarified the Sedlmeier and Renkewitz Table
16.1/16.2 distinction.
cofad 0.3.3
- report correct df for t test
cofad 0.3.2
cofad 0.3.1
- fix github action for joss paper
- fix some typos
- add install instructions for cran
- remove rtools instructions (only relevant for dev version)
- change order of condition variable for akan data set
- add Maraver 2021 data set
cofad 0.3.0
- several bugs were fixed including rare occasions, where the order of
factors was not treated correctly
- included a helper function to calculate differences between two sets
of lambdas for a competing contrast analysis, including
documentation
- added data examples
- remove plyr as dependency
- spell check
- change maintainer to Johannes Titz, change order of authors, add
contributors Mirka Henninger and Simone Malejka
- improve summary functions, content and display
- modify shiny GUI to use normal elements due to instability with
moving elements (sortable)
- migrate to shinytest2
- include test for aggregated function, make it work with summary
- deduplicate code (reuse between for mixed)
- update summary for mixed
cofad 0.2.1
- small improvements in documentation, references and paper for the
official publication at journal of open source software
cofad 0.2.0
- Added a
NEWS.md file to track changes to the
package.
- Added Shiny GUI.
- Improved structure of the package.
- Fixed Bug with 0-variance conditions.
- Improved README.
- Improved examples.
- Improved documentation.
- Added and documented data sets.
- Added function for aggregated data.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.