Maximilian Linde

About me

Maximilian Linde

PhD student

University of Groningen

I am a PhD student at the Psychometrics & Statistics group at the faculty of Behavioural & Social Sciences at the University of Groningen, under the supervision of Don van Ravenzwaaij, Jorge N. Tendeiro, and Rob R. Meijer.

In my PhD project, I am developing easy-to-use Bayesian statistical techniques and software for research in the biomedical sciences (but also other fields). A major focus lies on reducing complexity and increasing user-friendliness, in order to reach a wide audience of researchers.

Apart from that, I am very enthusiastic about statistics/data science/machine learning and programming in general, and I take active steps to expand my horizon and learn as much as possible.

Academic

The work for my PhD focuses on Bayesian inference primarily for the biomedical sciences. More specifically, I develop software and tools that aim to make the application of Bayesian techniques simpler for researchers who are not statistical experts. At this point, this accumulated in the baymedr R package (see also here) and a corresponding baymedr web application (see also here).

See below for my academic output and activity.

Software

Linde, M., & van Ravenzwaaij, D. (2021). baymedr: Computation of Bayes factors for common biomedical designs. R package version 0.1.1. https://CRAN.R-project.org/package=baymedr
Linde, M., & van Ravenzwaaij, D. (2021). baymedr web application. https://maxlinde.shinyapps.io/baymedr

Publications

Linde, M., Tendeiro, J. N., Selker, R., Wagenmakers, E.-J., & van Ravenzwaaij, D. (2021). Decisions about equivalence: A comparison of TOST, HDI-ROPE, and the Bayes factor. Psychological Methods

Manuscript Preprint Code
Linde, M., & van Ravenzwaaij, D. (2021). Bayes factor model comparisons across parameter values for mixed models. Computational Brain & Behavior

Manuscript Preprint Code
Field, S. M.*, Hoek, J.*, de Vries, Y. A., Linde, M., Pittelkow, M.-M., Muradchanian, J., & van Ravenzwaaij, D. (2021). Rethinking Remdesivir for COVID-19: A Bayesian reanalysis of trial findings. PLOS ONE, 16, e0255093.

Manuscript Preprint Code
Heck, D. W., Boehm, U. Böing-Messing, F., Bürkner, P. C., Derks, K., Dienes, Z., Fu, Q., Gu, X., Karimova, D., Kiers, H. A. L., Klugkist, I., Kuiper, R. M., Lee, M. D., Leenders, R., Leplaa, H. J., Linde, M., Ly, A., Meijerink-Bosman, M., Moerbeek, M., Mulder, J., Palfi, B., Schönbrodt, F. D., Tendeiro, J. N., van den Bergh, D., van Lissa, C., van Ravenzwaaij, D., Vanpaemel, W., Wagenmakers, E.-J., Williams, D. R., Zondervan-Zwijnenburg, M., & Hoijtink, H. (2021). A review of applications of the Bayes factor in psychological research. In press.

Preprint Code
Linde, M., & van Ravenzwaaij, D. (2022). baymedr: An R package for the calculation of Bayes factors for equivalence, non-inferiority, and superiority designs. Submitted for publication.

Preprint

Projects

baymedr

R package for the calcultion of Bayes factors for common biomedical designs.

Check source code Check CRAN

baymedr Shiny App

Corresponding Shiny web application for the baymedr R package.

Check source code Check app

My Portfolio

Code for my portfolio, which partly serves for me to learn the basics of front-end web development.

Check source code

About me