Stef van Buuren

Stef van Buuren

4 packages on CRAN

AGD

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Tools for the analysis of growth data: to extract an LMS table from a gamlss object, to calculate the standard deviation scores and its inverse, and to superpose two wormplots from different models. The package contains a some varieties of reference tables, especially for The Netherlands.

dscore

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The D-score is a quantitative measure of child development. The D-score follows the Rasch model. See Jacobusse, van Buuren and Verkerk (2006) <doi:10.1002/sim.2351>. The user can convert milestone scores from 19 assessment instruments into the D-score and the DAZ (D-score adjusted for age). Several tools assist in mapping milestone names into the 9-position Global Scale of Early Development (GSED) convention. Supports calculation of the D-score using 'dutch' <doi:10.1177/0962280212473300>, 'gcdg' <doi:10.1136/bmjgh-2019-001724> and 'gsed' conversion keys. The user can calculate DAZ using 'dutch' and 'gcdg' age-conditional references.

mice

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Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.

miceExt

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Extends and builds on the 'mice' package by adding a functionality to perform multivariate predictive mean matching on imputed data as well as new functionalities to perform predictive mean matching on factor variables.