Open AccessModeling event count data in the presence of informative dropout with application to bleeding and transfusion events in myelodysplastic syndrome
Author(s) -
G. Diao,
D. Zeng,
K. Hu,
J.G. Ibrahim
Publication year - 2017
Publication title -
carolina digital repository (university of north carolina at chapel hill)
Language(s) - English
DOI - 10.17615/xxhk-5214
Subject(s) - dropout (neural networks) , medicine , myelodysplastic syndromes , event (particle physics) , count data , statistics , computer science , bone marrow , mathematics , machine learning , physics , quantum mechanics , poisson distribution