A tool to easily simulate valid experimental data
Simulation is often employed in statistics to empirically quantify and understand the performance of various statistical methods. Simulating data is advisable as another diagnostic tool for experimental design to ensure the collected experimental data can be effectively analysed in accordance with their intended goals. Nevertheless, simulating data requires effort, particularly for novices, thus presenting a challenge in routine adoption. In this talk, I present a tool, implemented in the edibble R-package, that easily simulates experimental data that respects the experimental structure and other encodings. The automated simulation scheme can make use of information that the user already prespecified as part of their experimental design, thus requiring little extra effort for the user to simulate experimental data.
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