4 papers
Artificial intelligence surrogates for treatment effect estimation with before-and-after data
Frances Dean, Anna Neufeld, Joshua Barrios +2
Estimating the causal effects of medical treatments is difficult when clinically important outcomes are costly to measure or require long follow-up. Short-term or inexpensive surro…
Inference conditional on selection: a review
Anna Neufeld, Ronan Perry, Daniela Witten
In this article, we review selective inference, a set of techniques for inference when the statistical question asked is a function of the data. This setting often arises in contem…
Do We Really Even Need Data? A Modern Look at Drawing Inference with Predicted Data
Stephen Salerno, Kentaro Hoffman, Awan Afiaz +3
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 ra…
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…