11 citations · 16 across the 9 of their papers we have counts for
12 papers · 1 filter
Assessing mediation in cross-sectional stepped wedge cluster randomized trials
Zhiqiang Cao, Fan Li
Mediation analysis has been comprehensively studied for independent data but relatively little work has been done for correlated data, especially for the increasingly adopted stepp…
How should parallel cluster randomized trials with a baseline period be analyzed? A survey of estimands and common estimators
Kenneth Menglin Lee, Fan Li
The parallel cluster randomized trial with baseline (PB-CRT) is a common variant of the standard parallel cluster randomized trial (P-CRT). We define two natural estimands in the c…
What's the Weight? Estimating Controlled Outcome Differences in Complex Surveys for Health Disparities Research
Stephen Salerno, Emily K. Roberts, Belinda L. Needham +4
In this work, we are motivated by the problem of estimating racial disparities in health outcomes, specifically the average controlled difference (ACD) in telomere length between B…
Power calculation for cross-sectional stepped wedge cluster randomized trials with a time-to-event endpoint
Mary Ryan Baumann, Denise Esserman, Monica Taljaard +1
Stepped wedge cluster randomized trials (SW-CRTs) are a form of randomized trial whereby clusters are progressively transitioned from control to intervention, with the timing of tr…
Group sequential two-stage preference designs
Ruyi Liu, Fan Li, Denise Esserman +1
The two-stage preference design (TSPD) enables the inference for treatment efficacy while allowing for incorporation of patient preference to treatment. It can provide unbiased est…
Maintaining the validity of inference from linear mixed models in stepped-wedge cluster randomized trials under misspecified random-effects structures
Yongdong Ouyang, Monica Taljaard, Andrew B Forbes +1
Linear mixed models are commonly used in analyzing stepped-wedge cluster randomized trials (SW-CRTs). A key consideration for analyzing a SW-CRT is accounting for the potentially c…