Showing 2024 · stat.MEShow all
3 papers · 2 filters
stat.ME2024
ipd: An R Package for Conducting Inference on Predicted Data
Stephen Salerno, Jiacheng Miao, Awan Afiaz +5
Summary: ipd is an open-source R software package for the downstream modeling of an outcome and its associated features where a potentially sizable portion of the outcome data has…
stat.ME2024
Some models are useful, but for how long?: A decision theoretic approach to choosing when to refit large-scale prediction models
Kentaro Hoffman, Stephen Salerno, Jeff Leek +1
Large-scale prediction models using tools from artificial intelligence (AI) or machine learning (ML) are increasingly common across a variety of industries and scientific domains.…
stat.ME2024
Do We Really Even Need Data?
Kentaro Hoffman, Stephen Salerno, Awan Afiaz +2
As artificial intelligence and machine learning tools become more accessible, and scientists face new obstacles to data collection (e.g. rising costs, declining survey response rat…