JMP Clinical Starter | Data Quality and Fraud

Data Quality and Fraud
Click on a button corresponding to a fraud detection process. Refer to the table below for guidance.
Constructs a cross domain data set and computes a distance matrix and performs hierarchical clustering of subjects across all of the study centers to identify pairs of subjects with a very small distance. This could be an indication that these subjects are in fact the same individual who has enrolled at multiple sites.
Comparing the distribution of study visit days for each center compared to all other centers combined, and identifying unusual differences (for example, a site where all visits occur on the same study day)
Calculating Mahalanobis distance based on available data to detect subject inliers and outliers in multivariate space, and generating results by site to see which sites are extreme
See the JMP Clinical Starter main page for other process categories.