The goal of multiple imputation is to provide valid inferences for statistical estimates from
incomplete data. To achieve that goal, imputed values should preserve the structure in the …

Informed by the theoretical lens of opportunity hoarding, this study considers whether STEM
postsecondary fields stand apart via the disproportionate exclusion of Black and Latina/o …

The impact of missing data on quantitative research can be serious, leading to biased
estimates of parameters, loss of information, decreased statistical power, increased standard …

Background Although exposure to natural outdoor environments has been consistently
associated with improved perceived general health, available evidence on a protective …

Multiple imputation by chained equations is a flexible and practical approach to handling
missing data. We describe the principles of the method and show how to impute categorical …

Background Multiple imputation is a commonly used method for handling incomplete
covariates as it can provide valid inference when data are missing at random. This depends …

Objective To determine outcomes at age 3 years in babies born before 27 completed weeks'
gestation in 2006, and to evaluate changes in outcome since 1995 for babies born between …

Identifying the types of mathematics content knowledge that are most predictive of students'
long-term learning is essential for improving both theories of mathematical development and …

Multiple imputation for missing data in epidemiological and clinical research: potential and
pitfalls | The BMJ Skip to main content Intended for healthcare professionals Access provided by …

Taking out student loans to assist with the costs of postsecondary schooling in the US has
become the norm in recent decades. The debt burden young adults acquire during the …