dfish

General code for hierarchical/multilevel data generation: ``` function sample_parms(group_dists, parm_names, cond_idx) parm_vals = map(d -> rand(d[cond_idx]), values(group_dists)) return NamedTuple{parm_names}(parm_vals) end function sample_condition_parms(group_dists, parm_names, n_subjects, cond_idx) return [sample_parms(group_dists, parm_names, cond_idx) for...

~~@DominiqueMakowski, I think the code above checks most of the boxes. The example is a within subjects 2X2 factorial design which affects one of the drift rates. The setup works...

I appreciate the vote of confidence. I fixed one issue and realized there is another one. Basically, I need to figure how to handle conditions for vector parameters. For example,...

The code above works well for between subject designs, but adapting to for within subject designs is more challenging. S The example above is a 2X2 between subject design where...

Thanks for taking the lead on this. From what I understand HCubature.jl is a good option. One thing to be aware of is that this type of numerical integration may...