Missing Data and Prediction. R packages psfmi and miceafter.

Joined January 2015
12 Photos and videos
Martijn Heymans retweeted
In AJE: Missing data? Don't drop observations! A longitudinal study in @hrsisr shows multiple imputation with predictive mean matching performs well, is easy to implement, and helps recover unbiased results doi.org/10.1093/aje/kwad139

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Just released on cran, psfmi package version 1.4.0 including new possibility to pool and select stratified Cox models after Multiple Imputation #rstats mwheymans.github.io/psfmi/

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Martijn Heymans retweeted
Replying to @RoelWing
@RoelWing just published his last PhD paper in the @JPhysiother! A prognostic model for neck-related disability in patients with sub-acute neck pain was externally validated at 6 weeks with acceptable discrimination and calibration. sciencedirect.com/science/ar…
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Martijn Heymans retweeted
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models jclinepi.com/article/S0895-4…

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Martijn Heymans retweeted
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Proud to present this paper about Handling Missing Data in Clinical Research as a Key Concept in Clinical Epidemiology @JClinEpi eur04.safelinks.protection.o…

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Do not dichotomize variables! Read here why, including easy to understand explanation and interpretation of linear and restricted cubic splines R code. frontiersin.org/articles/10.…

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Excited to share this NEW PAPER about pooling and selecting prognostic/prediction models after Multiple Imputation using the median of p-values rule (MPR) that outperforms more complex methods. eur04.safelinks.protection.o…

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Martijn Heymans retweeted
27 Jul 2022
We are excited to announce that RStudio, PBC will become Posit, PBC in October! More information here: rstudio.com/blog/rstudio-is-…
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Working with R code makes you think...should I change my name into M>artijn ?
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Martijn Heymans retweeted
Reminder: Tomorrow is the follow-up session to the 'Meta-Analysis with R' workshop I gave prior to #ESMARConf2022. Details here: wvbauer.com/doku.php/worksho… We will continue where I left off (see here for the materials covered so far: github.com/wviechtb/esmarcon…).
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Martijn Heymans retweeted
Missing data was handled inconsistently in UK prediction models: a review of method used jclinepi.com/article/S0895-4…

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Martijn Heymans retweeted
Attending the online @APH Methodology tutorial by @JudithRijnhart: about the robustness of #multiverse analysis - assessing the effect of the researcher's degrees of freedom on the #replicability of an analysis. with @judithbosmans link.springer.com/article/10…
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