It is increasingly important to accurately and comprehensively estimate the effects of
particular clinical treatments. Although randomization is the current gold standard …

Missing data are ubiquitous in medical research, yet there is still uncertainty over when
restricting to the complete records is likely to be acceptable, when more complex methods …

Background Data on the effectiveness of oral antivirals in patients with mild-to-moderate
COVID-19 are urgently needed. This retrospective cohort study aimed to evaluate the …

Missing data are ubiquitous in medical research. Although there is increasing guidance on
how to handle missing data, practice is changing slowly and misapprehensions abound …

The elevated risk of Parkinson's disease in patients with diabetes might be mitigated
depending on the type of drugs prescribed to treat diabetes. Population data for risk of …

Multiple Imputation and its Application The most up-to-date edition of a bestselling guide to
analyzing partially observed data In this comprehensively revised Second Edition of Multiple …

Randomized clinical trials (RCT) are accepted as the gold-standard approaches to measure
effects of intervention or treatment on outcomes. They are also the designs of choice for …

Propensity score analysis is a popular method to control for confounding in observational
studies. A challenge in propensity methods is missing values in confounders. Several …

CPX-351 and venetoclax and azacitidine (ven/aza) are both indicated as initial therapy for
acute myeloid leukemia (AML) in older adults. In the absence of prospective randomized …

Acquiring real-world evidence is crucial to support health policy, but observational studies
are prone to serious biases. An approach was recently proposed to overcome confounding …