2 citations · 3 across the 4 of their papers we have counts for
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stat.ME2019
A review and evaluation of standard methods to handle missing data on time-varying confounders in marginal structural models
Clemence Leyrat, James R Carpenter, Sebastien Bailly +1
Marginal structural models (MSMs) are commonly used to estimate causal intervention effects in longitudinal non-randomised studies. A common issue when analysing data from observat…
stat.ME2019★ 2 cited
Propensity scores using missingness pattern information: a practical guide
Helen A. Blake, Clemence Leyrat, Kathryn E. Mansfield +4
Electronic health records are a valuable data source for investigating health-related questions, and propensity score analysis has become an increasingly popular approach to addres…