Missing data present a perennial challenge in scientific research, potentially undermining the validity of conclusions if not addressed rigorously. The analysis of missing data encompasses a broad ...

This kind of exploratory data analysis depends on effective visualization techniques. In our case, the key design advance was the Group-in-a-Box layout technique, which presents the results of ...

Make the transition from psychology student to data scientist with our MSc. This course combines practical training in the latest research techniques with classes in computational data analysis.

SM seeks qualitative and quantitative contributions that address the full range of methodological problems confronted by empirical research in the social sciences, including conceptualization, data ...

Four integrative data analysis strategies for mixed-method evaluation designs are derived from and illustrated by empirical practice: data transformation, typology development, extreme case analysis, ...

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 ...