5 papers
Nearly optimal capture-recapture sampling and empirical likelihood weighting estimation for M-estimation with big data
Yan Fan, Yang Liu, Yukun Liu +1
Subsampling techniques can reduce the computational costs of processing big data. Practical subsampling plans typically involve initial uniform sampling and refined sampling. With…
Tuning-parameter-free optimal propensity score matching approach for causal inference
Yukun Liu, Jing Qin
Propensity score matching (PSM) is a pseudo-experimental method that uses statistical techniques to construct an artificial control group by matching each treated unit with one or…
A selective review on calibration information from similar studies based on parametric likelihood or empirical likelihood
Jing Qin, Yukun Liu, Pengfei Li
In multi-center clinical trials, due to various reasons, the individual-level data are strictly restricted to be assessed publicly. Instead, the summarized information is widely av…
Full-semiparametric-likelihood-based inference for non-ignorable missing data
Yukun Liu, Pengfei Li, Jing Qin
During the past few decades, missing-data problems have been studied extensively, with a focus on the ignorable missing case, where the missing probability depends only on observab…
Inference for case-control studies with incident and prevalent cases
Marlena Maziarz, Yukun Liu, Jing Qin +1
We propose and study a fully efficient method to estimate associations of an exposure with disease incidence when both, incident cases and prevalent cases, i.e. individuals who wer…