Assistant Professor, Department of Statistics @KState Ing. Agr. @AgronomiaUBA 🧉🇦🇷
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ALT In the past, we have designed experiments and gathered data on the hope that the results would lead to insight and possible publication—but then the actual data would end up too noisy, and we would realize in retrospect that our study never really had a chance of answering the questions we wanted to ask. Such an experience is not a complete waste— we learn from our mistakes and can use them to design future studies—but we can often do better by preceding any data collection with a computer simulation. Simulating a study can be more challenging than conducting a traditional power analysis. The simulation does not require any mathematical calculations; the challenge is the need to specify all aspects of the new study. For example, if the analysis will use regression on pre-treatment predictors, these must be simulated too, and the simulated model for the outcome should include the possibility of interactions. Beyond the obvious benefit of revealing designs that look to be too noisy to de
ALT Pooh and Piglet walking the wood. "Pooh?" said Piglet. "Yes, Piglet?" said Pooh. "27417 parameters," said Piglet. "Oh bother," said Pooh. Scientifically informed data analysis sometimes is inconvenient, but it's out duty to do the best we can, no matter the inconvenience.
