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alphaN

Set Alpha Based on Sample Size Using Bayes Factors

v0.1.2 · Jul 13, 2025 · MIT + file LICENSE

Description

Sets the alpha level for coefficients in a regression model as a decreasing function of the sample size through the use of Jeffreys' Approximate Bayes factor. You tell alphaN() your sample size, and it tells you to which value you must lower alpha to avoid Lindley's Paradox. For details, see Wulff and Taylor (2024) <doi:10.1177/14761270231214429>.

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0

Last 30 days

25

Last 90 days

189

Last year

Trend: -100% (30d vs prior 30d)

autoCRAN

5

Last 7 days

22

Last 30 days

1

All-time

autoCRAN-only: this name is served only by autoCRAN, so the count is exact.

CRAN Check Status

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Code

Structure

Lines of code

743

Files

32

Compiled share

0%

Has compiled src

No

Language breakdown

R 272 (36.6%)Tests 152 (20.5%)Docs 234 (31.5%)Vignettes 85 (11.4%)

API

Exported functions

6

Internal functions

0

Recent export changes

v0.1.0+6 JAB, JAB_plot, JABp +3 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.56

testthat edition

3

CI present

No

CI type

[]

PR gated

No

Docs

Return-value doc rate

100%

\dontrun example ratio

0%

Roxygen coverage

100%

Has pkgdown

No

NEWS present

Yes

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

Unsafe pattern score

0

Dep constraint coverage

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

System requirements

C++ standard

License

MIT + file LICENSE

License flags

SPDX valid, OSI approved

History

Versions

2

First release

2023-01-12

Latest release

2025-07-13

Avg cadence

913 days

Cold removal rate

Dep drift

0

LOC over versions

v0.1.0: 799 LOCv0.1.2: 743 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/cran-code-metrics.

Version History

3 tracked
new 0.1.2 Mar 10, 2026
updated 0.1.2 ← 0.1.0 diff Jul 12, 2025
new 0.1.0 Jan 11, 2023