533 citations
- Cornell UniversityUS77 papers
- Harvard UniversityUS11 papers
- Stanford UniversityUS9 papers
- CitigroupUS7 papers
- Columbia UniversityUS7 papers
- Massachusetts Institute of TechnologyUS7 papers
- Memorial Sloan Kettering Cancer CenterUS7 papers
- The University of Texas at AustinUS7 papers
- University of PennsylvaniaUS7 papers
- Georgia Institute of TechnologyUS6 papers
- Icahn School of Medicine at Mount SinaiUS6 papers
- Mayo ClinicUS6 papers
Showing 2017 · stat.MEShow all
2 papers · 2 filters
stat.ME2017★ 11 cited
On the number of principal components in high dimensions
Sungkyu Jung, Myung Hee Lee, Jeongyoun Ahn
We consider the problem of how many components to retain in the application of principal component analysis when the dimension is much higher than the number of observations. To es…
stat.ME2017
Doubly Robust Inference for Targeted Minimum Loss Based Estimation in Randomized Trials with Missing Outcome Data
Iván Díaz, Mark J. van der Laan
Missing outcome data is one of the principal threats to the validity of treatment effect estimates from randomized trials. The outcome distributions of participants with missing an…