Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (11.7%) to scientific vocabulary
Repository
Principle Components Auxiliary Variables
Basic Info
Statistics
- Stars: 0
- Watchers: 1
- Forks: 2
- Open Issues: 5
- Releases: 6
Metadata Files
README.md
PcAux
Principal Component Auxiliary Variables
This is the repository for the PcAux package which was formerly called "quark."
PcAux assists in automatically extracting auxiliary features for simple, principled missing data imputation.
PcAux is beta software. Please report any issues that you encounter. You may also suggest new features.
Thank you for your interest in PcAux! We hope you find our software useful!
Installation
The PcAux package can be installed from GitHub using one of the following
methods:
pak
pak::pkg_install("Statscamp/PcAux")
devtools
devtools::install_github("Statscamp/PcAux")
remotes
remotes::install_github("Statscamp/PcAux")
Documentation
You can find detailed documentation here. We are working diligently to move the documentation directly into the package.
Example
A basic missing data treatment using PcAux might look like the following:
Load the
PcAuxLibrarylibrary(PcAux)Load and prepare your data: ``` data(sample1)
Examine the sample data
head(sample1) summary(sample1)
Create variables to pass as function parameters
List of nominal variables included in imputation
myNoms <- c("male","incident")
List of ordinal variables included in imputation
myOrds <- c("grade")
Exclude row id variables from the imputation
myIds <- c("ID")
List of other variables to exclude from imputation
myDrops <- c("Qual")
List of moderators you plan on using in your analysis model
myMods <- c("grade","incident") ```
Create the PcAux object by passing the raw data and function parameters to
prepDatapcaux_obj1 <- prepData( rawData = sample1, moderators = myMods, nomVars = myNoms, ordVars = myOrds, idVars = myIds, dropVars = myDrops )Create a set of principal component auxiliary variables
pcaux_obj2 <- createPcAux( pcAuxData = pcaux_obj1, nComps = c(Inf, Inf), interactType = 2, maxPolyPow = 1, control = list(minItemPredCor = .3) )Finally, use the principal component auxiliaries as the predictors in a multiple imputation run:
pcaux_obj3 <- miWithPcAux( rawData = sample1, pcAuxData = pcaux_obj2, nComps = c(.6, .5), nImps = 10 )
You can work directly with the principal component auxiliaries by merging them directly back into the raw data:
outData <- mergePcAux(pcAuxData = pcaux_obj3, rawData = sample1)
Owner
- Login: Statscamp
- Kind: user
- Repositories: 1
- Profile: https://github.com/Statscamp
Citation (CITATION.cff)
# -----------------------------------------------------------
# CITATION file created with {cffr} R package, v0.4.1
# See also: https://docs.ropensci.org/cffr/
# -----------------------------------------------------------
cff-version: 1.2.0
message: 'To cite package "PcAux" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'PcAux: Principle Components Auxiliary Variables'
version: 0.9.22
abstract: Automatically extract auxiliary features for simple, principled missing
data analysis.
authors:
- family-names: Lang
given-names: Kyle
email: k.m.lang@uvt.nl
- family-names: Little
given-names: Todd
email: todd.little@ttu.edu
repository-code: https://github.com/Statscamp/PcAux
url: https://github.com/Statscamp/PcAux
contact:
- family-names: Squire
given-names: Danny
email: danny.squire@ttu.edu
references:
- type: software
title: 'R: A Language and Environment for Statistical Computing'
notes: Depends
url: https://www.R-project.org/
authors:
- name: R Core Team
location:
name: Vienna, Austria
year: '2023'
institution:
name: R Foundation for Statistical Computing
version: '>= 3.5.0'
- type: software
title: coop
abstract: 'coop: Co-Operation: Fast Covariance, Correlation, and Cosine Similarity
Operations'
notes: Imports
url: https://github.com/wrathematics/coop
repository: https://CRAN.R-project.org/package=coop
authors:
- family-names: Schmidt
given-names: Drew
email: wrathematics@gmail.com
year: '2023'
- type: software
title: ICC
abstract: 'ICC: Facilitating Estimation of the Intraclass Correlation Coefficient'
notes: Imports
url: https://github.com/matthewwolak/ICC
repository: https://CRAN.R-project.org/package=ICC
authors:
- family-names: Wolak
given-names: Matthew
email: matthewwolak@gmail.com
year: '2023'
- type: software
title: methods
abstract: 'R: A Language and Environment for Statistical Computing'
notes: Imports
authors:
- name: R Core Team
location:
name: Vienna, Austria
year: '2023'
institution:
name: R Foundation for Statistical Computing
- type: software
title: mice
abstract: 'mice: Multivariate Imputation by Chained Equations'
notes: Imports
url: https://amices.org/mice/
repository: https://CRAN.R-project.org/package=mice
authors:
- family-names: van Buuren
given-names: Stef
email: stef.vanbuuren@tno.nl
- family-names: Groothuis-Oudshoorn
given-names: Karin
email: c.g.m.oudshoorn@utwente.nl
year: '2023'
- type: software
title: parallel
abstract: 'R: A Language and Environment for Statistical Computing'
notes: Imports
authors:
- name: R Core Team
location:
name: Vienna, Austria
year: '2023'
institution:
name: R Foundation for Statistical Computing
- type: software
title: purrr
abstract: 'purrr: Functional Programming Tools'
notes: Imports
url: https://purrr.tidyverse.org/
repository: https://CRAN.R-project.org/package=purrr
authors:
- family-names: Wickham
given-names: Hadley
email: hadley@rstudio.com
orcid: https://orcid.org/0000-0003-4757-117X
- family-names: Henry
given-names: Lionel
email: lionel@rstudio.com
year: '2023'
- type: software
title: rlecuyer
abstract: 'rlecuyer: R Interface to RNG with Multiple Streams'
notes: Imports
url: http://www.iro.umontreal.ca/~lecuyer/myftp/papers/streams00.pdf
repository: https://CRAN.R-project.org/package=rlecuyer
authors:
- family-names: Sevcikova
given-names: Hana
email: hanas@uw.edu
- family-names: Rossini
given-names: Tony
email: anthony.rossini@novartis.com
year: '2023'
- type: software
title: stats
abstract: 'R: A Language and Environment for Statistical Computing'
notes: Imports
authors:
- name: R Core Team
location:
name: Vienna, Austria
year: '2023'
institution:
name: R Foundation for Statistical Computing
- type: software
title: utils
abstract: 'R: A Language and Environment for Statistical Computing'
notes: Imports
authors:
- name: R Core Team
location:
name: Vienna, Austria
year: '2023'
institution:
name: R Foundation for Statistical Computing
- type: software
title: vcd
abstract: 'vcd: Visualizing Categorical Data'
notes: Imports
repository: https://CRAN.R-project.org/package=vcd
authors:
- family-names: Meyer
given-names: David
email: David.Meyer@R-project.org
orcid: https://orcid.org/0000-0002-5196-3048
- family-names: Zeileis
given-names: Achim
email: Achim.Zeileis@R-project.org
orcid: https://orcid.org/0000-0003-0918-3766
- family-names: Hornik
given-names: Kurt
email: Kurt.Hornik@R-project.org
orcid: https://orcid.org/0000-0003-4198-9911
year: '2023'
GitHub Events
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Dependencies
- R >= 3.5.0 depends
- ICC * imports
- coop * imports
- methods * imports
- mice * imports
- parallel * imports
- purrr * imports
- rlecuyer * imports
- stats * imports
- utils * imports
- vcd * imports
- withr * imports