Biostatistics Weekly Seminar

Variable selection is often not needed, and a big model with all potentially relevant variables can be used. Such a big model can avoid overfitting if appropriate priors are used. Variable selection can be useful to reduce future measurement costs or improve explainability. If we have built a good big model with all variables, that can be used as a reference model, and we can condition the variable selection decision task on that reference model. Reference model approach greatly improves the stability of variable selection. I present the basic ideas and some recent advances in the reference model variable selection approach.

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24 August 2022
12:15pm