4 papers
A Bayesian approach to the survivor average causal effect in cluster-randomized crossover trials
Dane Isenberg, Michael O. Harhay, Andrew B. Forbes +3
In cluster-randomized crossover (CRXO) trials, groups of individuals are randomly assigned to two or more sequences of alternating treatments. Since clusters serve as their own con…
Estimating the average treatment effect in cluster-randomized trials with misclassified outcomes and non-random validation subsets
Dane Isenberg, Nandita Mitra, Steven C. Marcus +2
Randomized trials are viewed as the benchmark for assessing causal effects of treatments on outcomes of interest. Nonetheless, challenges such as measurement error can undermine th…
Integrating Misclassified EHR Outcomes with Validated Outcomes from a Non-probability Sample
Jenny Shen, Dane Isenberg, Kristin A. Linn +1
Although increasingly used for research, electronic health records (EHR) often lack gold-standard assessment of key data elements. Linking EHRs to other data sources with higher-qu…
Weighting methods for truncation by death in cluster-randomized trials
Dane Isenberg, Michael Harhay, Nandita Mitra +1
Patient-centered outcomes, such as quality of life and length of hospital stay, are the focus in a wide array of clinical studies. However, participants in randomized trials for el…