Showing 4 of total 4 results (show query)
alexanderrobitzsch
miceadds:Some Additional Multiple Imputation Functions, Especially for 'mice'
Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are implemented. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>), substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>), and features for the generation of synthetic datasets (Reiter, 2005, <doi:10.1111/j.1467-985X.2004.00343.x>; Nowok, Raab, & Dibben, 2016, <doi:10.18637/jss.v074.i11>).
Maintained by Alexander Robitzsch. Last updated 29 days ago.
missing-datamultiple-imputationopenblascpp
16 stars 9.16 score 542 scripts 9 dependents
ices-tools-prod
TAF:Transparent Assessment Framework for Reproducible Research
General framework to organize data, methods, and results used in reproducible scientific analyses. A TAF analysis consists of four scripts (data.R, model.R, output.R, report.R) that are run sequentially. Each script starts by reading files from a previous step and ends with writing out files for the next step. Convenience functions are provided to version control the required data and software, run analyses, clean residues from previous runs, manage files, manipulate tables, and produce figures. With a focus on stability and reproducible analyses, the TAF package comes with no dependencies. TAF forms a base layer for the 'icesTAF' package and other scientific applications.
Maintained by Arni Magnusson. Last updated 5 days ago.
3 stars 8.05 score 282 scripts 2 dependents
dbosak01
common:Solutions for Common Problems in Base R
Contains functions for solving commonly encountered problems while programming in R. This package is intended to provide a lightweight supplement to Base R, and will be useful for almost any R user.
Maintained by David Bosak. Last updated 12 months ago.
6 stars 7.98 score 193 scripts 12 dependentsices-tools-prod
icesTAF:Functions to Support the ICES Transparent Assessment Framework
Functions to support the ICES Transparent Assessment Framework <https://taf.ices.dk> to organize data, methods, and results used in ICES assessments. ICES is an organization facilitating international collaboration in marine science.
Maintained by Colin Millar. Last updated 2 years ago.
5 stars 6.37 score 1.1k scripts 1 dependents