Jason Izard, Andrea Hartzler, Daniel I Avery, Cheryl Shih, Bruce L Dalkin, John L Gore
User-centered design of quality of life reports for clinical care of patients with prostate cancer
Surgery
many commonly used mathematical models field mathematical biology involve challenges parameter nonidentifiability practical nonidentifiability quality quantity data provide sufficiently precise parameter estimates often encountered even relatively simple models particular situation parameters identifiable others often encountered work apply recent likelihoodbased workflow called profilewise analysis pwa nonidentifiable models first time pwa workflow addresses identifiability parameter estimation prediction unified framework simple implement interpret previous implementations workflow dealt idealised identifiable problems study illustrate pwa workflow applied structurally nonidentifiable practically nonidentifiable models context simple population growth models dealing simple mathematical models allows us present pwa workflow didactic selfcontained document studied together relatively straightforward julia code provided github working simple mathematical models allows pwa workflow prediction intervals compared gold standard full likelihood prediction intervals together examples illustrate pwa workflow provides us systematic way dealing nonidentifiability especially compared approaches seeking ad hoc parameter combinations simply setting parameter values arbitrary default value importantly show pwa workflow provides insight commonlyencountered situation parameters identifiable others allowing us explore uncertainty parameters combinations parameters regardless identifiability status influences model predictions way insightful interpretable