A synthetic, longitudinal athletic dataset generated through a transparent, rule-based simulation engine. Captures individual activity sessions across multiple athletes, environmental conditions, and physiological responses. Specifically designed as an alternative to legacy teaching datasets by introducing realistic hierarchical repeated measures, complex two-way covariate interactions, and a deliberate Missing Not At Random (MNAR) tracking mechanism suitable for advanced imputation workflows. Methodologies implemented are based on van Buuren (2018) <doi:10.1201/9780429492259> and Bates et al. (2015) <doi:10.18637/jss.v067.i01>.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | tibble, mice, modelsummary, lme4 |
| Suggests: | tidyverse |
| Published: | 2026-06-30 |
| DOI: | 10.32614/CRAN.package.sportsfeatures (may not be active yet) |
| Author: | Mohammad Abbas [aut, cre] |
| Maintainer: | Mohammad Abbas <ma.abbas3107 at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | sportsfeatures results |
| Reference manual: | sportsfeatures.html , sportsfeatures.pdf |
| Package source: | sportsfeatures_0.1.0.tar.gz |
| Windows binaries: | r-devel: sportsfeatures_0.1.0.zip, r-release: not available, r-oldrel: sportsfeatures_0.1.0.zip |
| macOS binaries: | r-release (arm64): sportsfeatures_0.1.0.tgz, r-oldrel (arm64): sportsfeatures_0.1.0.tgz, r-release (x86_64): sportsfeatures_0.1.0.tgz, r-oldrel (x86_64): sportsfeatures_0.1.0.tgz |
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