Optimize laboratory data management with Excel. This course offers tools and techniques for automating tasks and improving ...

Missing data are almost inevitable in medical research. This leads to a loss of power and potential bias. Multiple imputation is a widely-used and flexible approach for handling missing data.

Missing data are almost inevitable in medical research. This leads to a loss of power and potential bias. Multiple imputation is a widely-used and flexible approach for handling missing data.

In mobile computing era, human activity recognition is an important research area for eldercare and healthcare center. Activity recognition performance decrease while partial data are lost due to ...

Missing data occur for multiple reasons: 1. the variable of interest is not measured by the research team (e.g., forgetting to measure weight at baseline); 2. the study participant misses a scheduled ...

The most extensive research on Medicaid coverage to date found that it reduced the risk of death by 21 percent.

Short course looking in depth at the problem of missing data in research studies. Explores the different types of missing data and the reasons for this along with good and bad methods of dealing with ...

Ethics and dissemination The protocol was approved by the Clinical Research Ethics Committee of the Cork Teaching Hospitals. The trial has been registered at ClinicalTrials.gov. The findings from this ...

The aim of this research is, thus, to perform an extensive simulation study to compare the ability of different statistical approaches to account for missing data caused by attrition, when studying ...

Missing data is a common issue in community health and epidemiological studies. Direct removal of samples with missing data can lead to reduced sample size and information bias, which deteriorates the ...