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retestR

0.1.0CRAN

Model-Based Anomaly Detection for Repeat Test-Takers

install.packages("retestR")
Test coverage, method
89%of lines run by tests

Flags repeat test-takers whose second-attempt performance departs from what a growth model predicts, using independent evidence sources: model-expected score gain (accounting for regression to the mean, time between attempts and remediation), differential performance on exposed versus new items ...

Full description

Flags repeat test-takers whose second-attempt performance departs from what a growth model predicts, using independent evidence sources: model-expected score gain (accounting for regression to the mean, time between attempts and remediation), differential performance on exposed versus new items (Sinharay, 2017, <doi:10.3102/1076998616673872>), and differential response speed under a lognormal response-time model (van der Linden, 2006, <doi:10.3102/10769986031002181>). Evidence is combined into a risk index calibrated by parametric bootstrap under the no-misconduct model, so flagging thresholds carry explicit false-positive rates.

Maintainer
Daniel Edi
Latest release
8 Oct 2026
First release
8 Oct 2026

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More details
Releases
1
Needs compilation
No
Needs R
>= 4.1
Config/roxygen2/version
8.1.0
Subjects (1) Method, Subjects
Cite

Package

Run in R for the authors' preferred citation:

citation("retestR")
APA
Edi, D. (2026). retestR: Model-Based Anomaly Detection for Repeat Test-Takers (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.retestR
About

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA
Balamuta, J. J. (2026). R Observatory: Metrics for retestR version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-28. https://doi.org/10.5281/zenodo.21843040
About

From data release v2026-10-28, which the citation names so these numbers can be found later.

All 13 check platforms pass.

  • r-devel-linux-x86_64-debian-clang

    The unreleased R on Linux, x86_64, debian-clang

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    0.1.0
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    The unreleased R on Windows, x86_64

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    The previous release of R on macOS, arm64

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    The previous release of R on macOS, x86_64

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    The previous release of R on Windows, x86_64

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    The patched release of R on Linux, x86_64

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    The current release of R on macOS, arm64

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    The current release of R on macOS, x86_64

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    The current release of R on Windows, x86_64

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  • 13 OK

Check results on CRAN

Total downloads in the last 30 days
242It comes from CRAN alone. autoCRAN was counted over another window, so it is not added.

CRAN rank

18,621 of 26,530

  • CRAN

CRAN

242 downloads in the last 30 days

Rank
18,621 of 26,530

It is in the total. Take it out

autoCRAN

0 downloads in the last 7 days

It is not added because it has no figure for the last 30 days.

Over time

Compare downloads

Needs
2
Dependent packages
0
Suggested by
0
Needs (2)
  • stats
  • utils
Installing it adds
0 packages, 0 KB of source
Of those, need compilation
0
Optional extras (2)
Functions
16
Public exports
6
Lines of R code
476
Median complexity
2
Functions (16)
Size and composition

Lines by kind (846)

KindLinesShare
R code47656%
Tests496%
Documentation24929%
Guides729%

Lines by language

LanguageLinesShare
R52562%
Rd24929%
Vignettes729%

Languages are counted from file extensions.

Files
25
R functions
16
Object systems
S3: 2 methods
Complexity
Median
2
Mean
3.13
Highest
13
Median lines per function
10
About complexity

Cyclomatic complexity counts the independent paths through a function: 1 is a straight line, higher is harder to test. R functions only.

Call graph figures
R functions
16
Calls
13
Unconnected
3
Groups
2

The tests ran and coverage was measured.

Lines run by tests
88.8%
Expressions run by tests
89.2%
Exports named in tests
83.3%
Coverage by file (6)
Coverage run
Lines counted
250
Lines the tests ran
222
Tests passed
Yes
Measured with
covr 3.6.5 on R 4.6.1
Test suite
Has tests
Yes
Test frameworks
R scripts, 1 script file
Lines of tests
49
Test lines per line of code
0.1
Exports documented
100%
Arguments documented
84%
Return value documented
100%
Help pages with examples
100%
Examples run in checks
100%
Guides (1)
Other documentation
README
Yes, 401 words
Release notes file
Yes
Help pages
6
Lines of documentation
249
  • Daniel Edi

    Maintainer since 0.1.0 (2026), author, copyright holder

edidatasolutions / retestr on github.com

Stars
0
Forks
0
Open issues
0
Last commit
21 Oct 2026
Activity
Commits
–
Open pull requests
0
Tagged releases
0
Latest tagged release
–
Issues closed in
–
Pull requests closed in
–
Pull requests merged
–
Created
27 Sep 2026
Licence file reads as
–
Development practices (7)
KindFound
Continuous integrationGitHub Actions, R CMD check workflow
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
Governance and communityContributing guide
Docs sourcepkgdown
GitHub Pages site last deployed 2026-10-21
The repository has a site deploy workflow
pkgdown site last built 2026-10-21
CRAN release processcran-comments.md

Method, repository practices

Across edidatasolutions

Claude Codeat least 3 crediting itClaude CodeFirst seen 8 Oct 2026at least 3 crediting it
Claude Opus 5.5Claude Opus 5.58 Oct 2026 to 21 Oct 20263 commits

Tools

ToolFirst seenCommits crediting it
Claude Code8 Oct 20263 at least

Models

ModelCommitsFirst commitLast commitCredit lines of
Claude Opus 5.538 Oct 202621 Oct 2026Claude Code

Across edidatasolutions

R releases
  • On CRAN
  • Release
VersionReleasedR
0.1.0 current8 Oct 20264.6.1
Release notes (0.1.0)
  • Initial release.
  • Expected-gain model for repeaters fitted by marginal ML, robust to preknowledge (rt_fit()).
  • Posterior-predictive evidence: score gain, exposed-item performance, response speed (rt_evidence()).
  • Risk index calibrated by parametric bootstrap with explicit false-positive rates (rt_risk()).
  • Raw-gain baseline (rt_raw_gain()) and known-truth simulation (rt_simulate()).