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@chstock and I met, and we mostly discussed example datasets (#11). It is difficult to find a fully realized public dataset from a real clinical trial, and it is tricky to safely disclose an internal dataset for this purpose. So we think a hybrid real/simulated approach is worth pursuing, and Transcelerate data may be able to help. @chstock agreed to pursue this.
We agreed that #3 is completed (c.f. https://openpharma.github.io/brms.mmrm/articles/simulation.html). I will being working on #56 based on brm_simulate_prior(). When that part is successful, I will repeat the exercise using custom R code instead of brms for prior predictive simulations.
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@chstock and I met, and we mostly discussed example datasets (#11). It is difficult to find a fully realized public dataset from a real clinical trial, and it is tricky to safely disclose an internal dataset for this purpose. So we think a hybrid real/simulated approach is worth pursuing, and Transcelerate data may be able to help. @chstock agreed to pursue this.
We agreed that #3 is completed (c.f. https://openpharma.github.io/brms.mmrm/articles/simulation.html). I will being working on #56 based on
brm_simulate_prior()
. When that part is successful, I will repeat the exercise using custom R code instead ofbrms
for prior predictive simulations.Beta Was this translation helpful? Give feedback.
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