Sometimes exact values of data are unknown: medical studies looking at patient survival after intervention, product reliability studies looking at failures for reliable products that don’t fail, or studies looking at contaminants below a detection limit. In these studies, simply removing data without exact values or substituting ad hoc values can lead to erroneous results. The inexact data in these studies are called censored or suspended data. Through case studies in this hands-on workshop, learn how censoring works and how to estimate distributions with censored data. Next, discover how JMP adapts models for analysis of variance or regression to handle inexact data.
