Missing data are a frequently encountered problem in epidemiologic and clinical research.1, 2 One approach is to include in the analysis only those participants without missing observations (complete ...

The analysis of missing data encompasses a broad spectrum of statistical methods designed to assess, mitigate, and rigorously quantify the uncertainty that arises when data points are absent.

A new publication by two University of Cincinnati researchers contends that adjusting how researchers approach their statistical analysis has the potential to change the lives of children and ...

Data sources The analysis in this report is based on the combination of work requirements and job skills data from the U.S. Department of Labor’s ... Methodology for O*NET analysis. By Rakesh Kochhar.

Researchers at China Pharmaceutical University have developed GseaVis, a user-friendly R package that significantly enhances ...

A common approach for APC analysis is multilevel modeling. A multilevel model is a kind of regression model that can be fit to data that is structured in “groups,” which themselves can be units of ...