Package: multimput 0.2.14

Thierry Onkelinx

multimput: Using Multiple Imputation to Address Missing Data

Accompanying package for the paper: Working with population totals in the presence of missing data comparing imputation methods in terms of bias and precision. Published in 2017 in the Journal of Ornithology volume 158 page 603–615 (<doi:10.1007/s10336-016-1404-9>).

Authors:Thierry Onkelinx [aut, cre], Koen Devos [aut], Paul Quataert [aut], Research Institute for Nature and Forest [cph, fnd]

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multimput.pdf |multimput.html✨
multimput/json (API)

# Install 'multimput' in R:

install.packages('multimput', repos = c('https://inbo.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/inbo/multimput/issues

Pkgdown:https://inbo.github.io

Datasets:

waterfowl - The observation pattern in the Flemish waterfowl dataset

On CRAN:

imputation imputation-model

3.32 score 1 stars 1 packages 14 scripts 9 exports 48 dependencies

Last updated 3 months agofrom:12d11eff38. Checks:OK: 4 ERROR: 2 WARNING: 1. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 03 2024
R-4.5-win	ERROR	Sep 25 2024
R-4.5-linux	OK	Dec 03 2024
R-4.4-win	OK	Dec 03 2024
R-4.4-mac	OK	Dec 03 2024
R-4.3-win	WARNING	Sep 25 2024
R-4.3-mac	ERROR	Dec 05 2024

Exports:aggregate_impute generate_data hurdle_impute impute missing_at_random missing_current_count missing_observed missing_volunteer model_impute

Dependencies:assertthat boot class classInt cli cpp11 DBI digest dplyr e1071 fansi fmesher generics glue INLA KernSmooth lattice lifecycle lme4 magrittr MASS Matrix MatrixModels minqa mvtnorm nlme nloptr pillar pkgconfig proxy purrr R6 Rcpp RcppEigen rlang s2 sf sp stringi stringr tibble tidyr tidyselect units utf8 vctrs withr wk

Model data with missing observations using multiple imputation

Thierry Onkelinx

Rendered fromimpute.Rmdusingknitr::rmarkdownon Dec 03 2024.

Last update: 2024-10-04
Started: 2022-02-03

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Aggregate an imputed dataset	aggregate_impute aggregate_impute,aggregatedImputed-method aggregate_impute,ANY-method aggregate_impute,rawImputed-method
The 'aggregatedImputed' class Holds an aggregated imputation data set	aggregatedImputed-class
Generate simulated data	generate_data
Combine two models into a hurdle model	hurdle_impute
Impute a dataset	impute impute,ANY-method impute,glmerMod-method impute,lm-method impute,maybeInla-method
The 'maybeInla' class	maybeInla-class
Generate missing data at random	missing_at_random
Generate missing data depending on the counts	missing_current_count
Generate missing data based on the observed patterns in the real dataset.	missing_observed
Generate missing data mimicking choices made by volunteers.	missing_volunteer
Model an imputed dataset	model_impute model_impute,aggregatedImputed-method model_impute,ANY-method
The 'rawImputed' class Holds a dataset and imputed values	rawImputed-class
The observation pattern in the Flemish waterfowl dataset	waterfowl