Background Missing data are common in medical research, which can lead to a loss in
statistical power and potentially biased results if not handled appropriately. Multiple …

Missing data commonly occur in large epidemiologic studies. Ignoring incompleteness or
handling the data inappropriately may bias study results, reduce power and efficiency, and …

Importance Out-of-hospital cardiac arrest is associated with low survival, but early
cardiopulmonary resuscitation (CPR) and defibrillation can improve outcomes if more widely …

Policy Points: Since 2012, Massachusetts law has provided legal protections against
discrimination on the basis of gender identity in employment, housing, credit, public …

Higher education researchers using survey data often face decisions about handling
missing data. Multiple imputation (MI) is considered by many statisticians to be the most …

Purpose: Enacted and anticipated stigma exist within healthcare settings for transgender
people, but research has yet to examine the effects of these forms of stigma on the …

Aim Defibrillation by bystanders and first responders has been associated with increased
survival, but limited data are available from non-metropolitan areas. We examined time from …

Importance Body dysmorphic disorder (BDD) is underrecognized and underdetected among
patients undergoing facial plastic and reconstructive surgery. Patients with BDD require …

Housing First (HF) is being widely disseminated in efforts to end homelessness among
homeless adults with psychiatric disabilities. This study evaluates the effectiveness of HF …

Multiple imputation (MI) is increasingly being used to handle missing data in epidemiologic
research. When data on both the exposure and the outcome are missing, an alternative to …