Lisa DeBruine
Lisa DeBruine
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Open-source tutorials benefit the field
Open research is increasingly required by journals and funders but involves many new skills. Creating open-source tutorials is useful to the field and personally rewarding, but these efforts must be credited accordingly.
Freda Wan
,
Wilhelmiina Toivo
,
Helena M. Paterson
,
Emily Nordmann
,
Phil McAleer
,
Kalliopi Mavromati
,
Rebecca J. Lai
,
Carolina E. Kuepper-Tetzel
,
Lisa DeBruine
,
James E. Bartlett
,
Dale J. Barr
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Project
Supplemental Materials
Code
DOI
Data visualisation using R, for researchers who don't use R
In this tutorial, we provide a practical introduction to data visualization using R specifically aimed at researchers who have little to no prior experience of using R.
Emily Nordmann
,
Phil McAleer
,
Wilhelmiina Toivo
,
Helena Paterson
,
Lisa DeBruine
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Project
Book
Code
Preprint
DOI
Improving Transparency, Falsifiability, and Rigor by Making Hypothesis Tests Machine-Readable
We examine what a machine-readable hypothesis test should look like and demonstrate the feasibility of machine-readable hypothesis tests in a real-life example using the fully operational prototype R package scienceverse.
Daniël Lakens
,
Lisa DeBruine
Preprint
R Package
Shiny App
DOI
Understanding mixed effects models through data simulation
How to simulate data with random-effects structure and analyze the data using linear mixed-effects regression, with a focus on interpreting the output in light of the simulated parameters.
Lisa DeBruine
,
Dale J Barr
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DOI
Preprint
Code
Shiny App
DOI
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