Jan De Neve


Jan De Neve graduated as a Master in Mathematics in 2007, a Master in Statistical Data Analysis in 2012 and obtained a PhD in Statistical Data Analysis in 2013 all at Ghent University. He is currently an assistant professor at the Data Analysis department of the faculty of Psychology and Educational Sciences.  


His research mainly concerns the development of semiparametric methods for the analysis of behavioral data. Using semiparametric theory, flexible statistical models can be developed that do not rely on stringent distributional assumptions. A key feature of his work is the use of ranks, which has three advantages: they are robust to outliers, they often result in increased efficiency and they exploit only the ordering of the data. This last feature is particularly relevant for the behavioral sciences where many data types are ordinal in nature. In addition to the theoretical development of methods, Jan De Neve also focuses on the implementation of statistical software packages in R.

Software development

  • pim, an R package to Fit Probabilistic Index Models
  • unifiedWMWqPCR, a unified Wilcoxon-Mann Whitney Test for testing differential expression in qPCR data