This large cross-sectional study examined the impact of COVID-19 emergency measures on
child/adolescent mental health for children/adolescents with and without pre-existing …

A common challenge in developmental research is the amount of incomplete and missing
data that occurs from respondents failing to complete tasks or questionnaires, as well as …

Background Missing data in costs and/or health outcomes and in confounding variables can
create bias in the inference of health economics and outcomes research studies, which in …

Background Robotic hepatectomy (RH) has been increasingly adopted for the treatment of
liver malignancies despite lacking evidence from randomised trials. We aimed to determine …

Background Many patients with acute low back pain (LBP) first seek care from primary care
physicians. Evidence is lacking for interventions to prevent transition to chronic LBP in this …

Missing data presents a significant challenge in statistical analysis and machine learning,
often resulting in biased outcomes and diminished efficiency. This comprehensive review …

Introduction The most prominent outcome measurement in the field of neuromodulation is
pain relief. Nevertheless, the number of studies that rely on composite outcomes has …

Abstract Background Patient Reported Outcomes (PRO) are gaining more and more
importance in the context of clinical trials. The assessment of PRO is frequently performed by …

Multiple imputation is a recommended method for handling incomplete data problems. One
of the barriers to its successful use is the breakdown of the multiple imputation procedure …

Background Research shows that adverse childhood experiences (ACEs) are problematic
and may impact delinquency and arrest in adolescence. However, resiliency theories …