6 citations · 6 across the 7 of their papers we have counts for
7 papers
The Subtype-Free Average Causal Effect for Heterogeneous Disease Etiology
Amit Sasson, Molin Wang, Shuji Ogino +1
Studies have shown that the effect an exposure may have on a disease can vary for different subtypes of the same disease. However, existing approaches to estimate and compare these…
A repeated measures approach to pooled and calibrated biomarker data
Abigail Sloan, Chao Cheng, Bernard Rosner +3
Participant level meta-analysis across multiple studies increases the sample size for pooled analyses, thereby improving precision in effect estimates and enabling subgroup analyse…
Spline Analysis of Biomarker Data Pooled From Multiple Matched/Nested Case-Control Studies
Yujie Wu, Mitchell H. Gail, Stephanie A. Smith-Warner +2
Pooling biomarker data across multiple studies enables researchers to get more precise estimates of the association between biomarker exposure measurements and disease risks due to…
Statistical methods for biomarker data pooled from multiple nested case-control studies
Abigail Sloan, Molin Wang
Pooling biomarker data across multiple studies allows for examination of a wider exposure range than generally possible in individual studies, evaluation of population subgroups an…
Semiparametric Methods for Exposure Misclassification in Propensity Score-Based Time-to-Event Data Analysis
Yingrui Yang, Molin Wang
In epidemiology, identifying the effect of exposure variables in relation to a time-to-event outcome is a classical research area of practical importance. Incorporating propensity…
A novel calibration framework for survival analysis when a binary covariate is measured at sparse time points
Daniel Nevo, Tsuyoshi Hamada, Shuji Ogino +1
The goals in clinical and cohort studies often include evaluation of the association of a time-dependent binary treatment or exposure with a survival outcome. Recently, several imp…