Package: codaredistlm 0.1.0

codaredistlm: Compositional Data Linear Models with Composition Redistribution

Provided data containing an outcome variable, compositional variables and additional covariates (optional); linearly regress the outcome variable on an isometric log ratio (ilr) transformation of the linearly dependent compositional variables. The package provides predictions (with confidence intervals) in the change (delta) in the outcome/response variable based on the multiple linear regression model and evenly spaced reallocations of the compositional values. The compositional data analysis approach implemented is outlined in Dumuid et al. (2017a) <doi:10.1177/0962280217710835> and Dumuid et al. (2017b) <doi:10.1177/0962280217737805>.

Authors:Ty Stanford [aut, cre], Charlotte Lund Rasmussen [aut], Dot Dumuid [aut]

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# Install 'codaredistlm' in R:
install.packages('codaredistlm', repos = c('https://tystan.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tystan/codaredistlm/issues

Datasets:
  • fairclough - Data from Fairclough (2017). Fitness, fatness and the reallocation of time between children's daily movement behaviours: an analysis of compositional data
  • fat_data - Randomly generated data to simulate child fat percentage regressed on time-use compositional data

On CRAN:

codacompositional-data-analysisisometric-log-ratiomultiple-linear-regressionplottingprediction

3.65 score 9 stars 8 scripts 234 downloads 2 exports 50 dependencies

Last updated 2 years agofrom:58879e1e12. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winOKNov 16 2024
R-4.5-linuxOKNov 16 2024
R-4.4-winOKNov 16 2024
R-4.4-macOKNov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:plot_delta_comppredict_delta_comps

Dependencies:backportsbayesmbroomclicolorspacecompositionscpp11DEoptimRdplyrevaluatefansifarvergenericsggplot2gluegtablehighrisobandknitrlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6RColorBrewerRcppRcppArmadillorlangrobustbasescalesstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithrxfunyaml