New statistical method handles tricky data types that stumped traditional models

Researchers have developed a regression technique for variables with natural limits—like survey scores capped at 100 or disease severity ratings. The advance could improve prediction accuracy in clinical trials, quality control testing, and any field where outcomes are bounded, potentially saving companies money on failed analyses and poor forecasts.

Originaltitel: Concave likelihood-based regression with finite-support response variables