Mattan Ben-shachar
Statistical Consultant & Research Analyst
Tel-Aviv, Tel-Aviv District, Israel
Summary
🤩
Rockstar🎓
Top SchoolMattan Ben-shachar is a statistical consultant and research analyst with eight years of experience helping social scientists turn complex data into reproducible, theory-driven insights, primarily using R. He teaches graduate and undergraduate statistics and R programming at Tel Aviv University and Ben-Gurion University while freelancing on applied projects ranging from (G)LMs and mixed models to Bayesian inference, SEM, GAMs and machine learning. An active open-source contributor to the easystats ecosystem, he has implemented Bayesian R2 and enhanced model-performance and visualization tooling used by the R community. His background as a PhD cognitive psychologist and former EEG researcher informs pragmatic pipelines and GUIs for data cleaning, visualization, and analysis that bridge methodological rigor and researcher needs. Colleagues know him for strong opinions on inference and reproducible research, and for turning methodological debates into practical, shareable code and teaching materials.
8 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Cognitive Psychology, Doctor of Philosophy - PhD, Cognitive Psychology at Ben-Gurion University of the Negev
English, Hebrew
Stackoverflow
1reputation
0reached
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Github Skills (17)
bayesian-statistics10
data-visualizations10
evaluation10
r10
statistics10
rs10
data-visualisation10
r-stats10
eval10
bayesian10
data-visualization10
ggplot10
machine-learning9
data-analysis9
performance-analysis8
Programming languages (9)
Github contributions (5)
easystats/easystats
Jul 2019 - Nov 2021
:milky_way: The R easystats-project
Role in this project:
Data Scientist
Data ScientistContributions:1 review, 57 commits, 1 PR in 2 years 4 months
Contributions summary:Mattan primarily contributed to generating and visualizing statistical data analysis results within the R environment. Their work involved the creation of advanced "cowplots" and other visualizations to represent data across different models and outcome types. The user implemented and updated figure generation code, refining plot aesthetics and incorporating specific statistical methods (p-values, Bayes Factors, etc.) into the visualization process. They also managed the creation of multiple figures and their layout for the project's documentation.
r-packagestatisticshypothesis-testingeasystatsregression-models
easystats/performance
Aug 2020 - Sep 2022
:muscle: Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)
Role in this project:Data Scientist
Data ScientistContributions:63 commits, 3 PRs, 51 pushes in 2 years 1 month
Contributions summary:Mattan primarily contributed to the `performance` repository by implementing and modifying functions related to Bayesian R2 calculation and model performance metrics. They added functionality for computing R2 for Bayesian models, specifically integrating with `BayesFactor`. The user also addressed issues related to model averaging and the inclusion of marginal R2 for models with random effects. Furthermore, they made revisions to accommodate changes in the `BayesFactor` package and enhanced the functionality of the `model_performance` function.
aicstatisticsmuscleeasystatsmodels
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