Importance Although several strategies of repetitive transcranial magnetic stimulation (rTMS)
have been investigated as treatment of major depressive disorder (MDD), their comparative …

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 …

Complete case analysis is widely used for handling missing data, and it is the default
method in many statistical packages. However, this method may introduce bias and some …

High quality protocols facilitate proper conduct, reporting, and external review of clinical
trials. However, the completeness of trial protocols is often inadequate. To help improve the …

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or
mean imputation, only work under highly restrictive conditions, which are often not met in …

High-frequency water quality monitoring systems provide valuable measurements for
predicting the trend of water quality, warning of abnormal activities or operating hydrological …

The last 20 years has seen an uptick in research on missing data problems, and most
software applications now implement one or more sophisticated missing data handling …

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 …

The most user-friendly and authoritative resource on missing data has been completely
revised to make room for the latest developments that make handling missing data more …

Overwhelming evidence shows the quality of reporting of randomised controlled trials
(RCTs) is not optimal. Without transparent reporting, readers cannot judge the reliability and …