5 citations · 7 across the 4 of their papers we have counts for
4 papers
Using Targeted Maximum Likelihood Estimation to Estimate Treatment Effect with Longitudinal Continuous or Binary Data: A Systematic Evaluation of 28 Diabetes Clinical Trials
Lingjing Jiang, Michael Rosenblum, Yu Du
The primary analysis of clinical trials in diabetes therapeutic area often involves a mixed-model repeated measure (MMRM) approach to estimate the average treatment effect for long…
Multi-Block Sparse Functional Principal Components Analysis for Longitudinal Microbiome Multi-Omics Data
Lingjing Jiang, Chris Elrod, Jane J. Kim +3
Microbiome researchers often need to model the temporal dynamics of multiple complex, nonlinear outcome trajectories simultaneously. This motivates our development of multivariate…
BayesTime: Bayesian Functional Principal Components for Sparse Longitudinal Data
Lingjing Jiang, Yuan Zhong, Chris Elrod +3
Modeling non-linear temporal trajectories is of fundamental interest in many application areas, such as in longitudinal microbiome analysis. Many existing methods focus on estimati…
Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data
Lingjing Jiang, Niina Haiminen, Anna-Paola Carrieri +7
Feature selection is indispensable in microbiome data analysis, but it can be particularly challenging as microbiome data sets are high-dimensional, underdetermined, sparse and com…