(2) We develop distributional theory for OLS estimators under measurement error and sparsity, finding that OLS estimators are subject to asymptotic bias even when they are consistent.
In the past decade, with the development of big data technology, an increasing amount of patient information has been stored as electronic health records (EHRs).
The Neyman Allocation and its conditional counterpart are used in many papers on experiment design, which typically assume that researchers have access to large pilot studies.
This paper introduces a transparent framework to identify the informational content of FOMC announcements.
However, a researcher that has chosen to cluster at the county level may be unsure of their decision, given knowledge that observations are independent across states.
This paper provides a user's guide to the general theory of approximate randomization tests developed in Canay, Romano, and Shaikh (2017) when specialized to linear regressions with clustered data.
Rare diseases affecting 350 million individuals are commonly associated with delay in diagnosis or misdiagnosis.
Many computational models were proposed to extract temporal patterns from clinical time series for each patient and among patient group for predictive healthcare.
Rare diseases affect a relatively small number of people, which limits investment in research for treatments and cures.