title: "To measure is to know. If you cannot measure it, you cannot improve it": statistical modeling cannot compensate for unmeasured bias.
authors.affiliation: Department of Surgery and Perioperative Sciences, Urology and Andrology, Umeå University, Umeå, Sweden; Department of Surgery, Urology Service, Memorial Sloan-Kettering Cancer Centre, New York, NY, USA. Electronic address: par.stattin@urologi.umu.se.
authors.forename: Pär
authors.initials: P
authors.lastname: Stattin
authors.affiliation: Department of Urology, New York University and Manhattan Veterans Affairs Medical Centre, New York, NY, USA.
authors.forename: Stacy
authors.initials: S
authors.lastname: Loeb
mesh_terms: D006801:Humans; D008297:Male; D057216:Propensity Score; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000401:mortality* / Q000601:surgery*