1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ME2023★ 1 cited
Kernel meets sieve: transformed hazards models with sparse longitudinal covariates
Dayu Sun, Zhuowei Sun, Xingqiu Zhao +1
We study the transformed hazards model with time-dependent covariates observed intermittently for the censored outcome. Existing work assumes the availability of the whole trajecto…
math.ST2023
Regression analysis of longitudinal data with mixed synchronous and asynchronous longitudinal covariates
Zhuowei Sun, Hongyuan Cao, Li Chen +1
In linear models, omitting a covariate that is orthogonal to covariates in the model does not result in biased coefficient estimation. This in general does not hold for longitudina…
stat.ME2023
Regression analysis of mixed sparse synchronous and asynchronous longitudinal covariates with varying-coefficient models
Congmin Liu, Zhuowei Sun, Hongyuan Cao
We consider varying-coefficient models for mixed synchronous and asynchronous longitudinal covariates, where asynchronicity refers to the misalignment of longitudinal measurement t…