131 citations · 352 across the 94 of their papers we have counts for
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Semiparametric efficient estimation of structural nested mean models with irregularly spaced observations
Shu Yang
Structural Nested Mean Models (SNMMs) are useful for causal inference of treatment effects in longitudinal observational studies. Most existing works assume that the data are colle…
Semiparametric estimation of structural failure time model in continuous-time processes
Shu Yang, Karen Pieper, Frank Cools
Structural failure time models are causal models for estimating the effect of time-varying treatments on a survival outcome. G-estimation and artificial censoring have been propose…
Integration of survey data and big observational data for finite population inference using mass imputation
Shu Yang, Jae Kwang Kim
Multiple data sources are becoming increasingly available for statistical analyses in the era of big data. As an important example in finite-population inference, we consider an im…
Combining multiple observational data sources to estimate causal effects
Shu Yang, Peng Ding
The era of big data has witnessed an increasing availability of multiple data sources for statistical analyses. We consider estimation of causal effects combining big main data wit…