agriDQ: Data Quality Checks and Statistical Assumption Testing for
Agricultural Experiments
Provides a comprehensive pipeline for data quality checks and
statistical assumption diagnostics in agricultural experimental data.
Functions cover outlier detection using Interquartile Range (IQR) fence,
Z-score, modified Z-score (Hampel identifier), Grubbs test and Dixon
Q-test with consensus flagging; missing data pattern analysis and
mechanism classification (Missing Completely At Random/Missing At
Random/Missing Not At Random (MCAR/MAR/MNAR)) via Little's test;
normality testing using Shapiro-Wilk, Anderson-Darling,
Kolmogorov-Smirnov, Lilliefors, Pearson chi-square and Jarque-Bera tests;
homogeneity of variance via Bartlett, Levene and Fligner-Killeen tests;
independence of errors via Durbin-Watson, Breusch-Godfrey and
Wald-Wolfowitz runs tests; experimental design validation for Completely
Randomised Design (CRD), Randomised Complete Block Design (RCBD), Latin
Square Design (LSD) and factorial designs; qualitative variable consistency
checks; and automated HyperText Markup Language (HTML) report generation.
Designed to align with Findable, Accessible, Interoperable and Reusable
(FAIR) data principles. Methods follow Gomez and Gomez (1984,
ISBN:978-0471870920) and Montgomery (2017, ISBN:978-1119492443).
| Version: |
0.1.3 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
stats, graphics, grDevices, utils, nortest, car, lmtest, tseries, stringdist |
| Suggests: |
testthat (≥ 3.0.0), covr, MASS |
| Published: |
2026-04-21 |
| DOI: |
10.32614/CRAN.package.agriDQ |
| Author: |
Sadikul Islam 
[aut, cre] |
| Maintainer: |
Sadikul Islam <sadikul.islamiasri at gmail.com> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
README, NEWS |
| CRAN checks: |
agriDQ results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=agriDQ
to link to this page.
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.