Mixture models for undiagnosed prevalent disease and interval-censored incident disease: applications to a cohort assembled from electronic health records

Statistics in Medicine

Volumn 36, Issue 22, 2017, Pages 3583-3595

  Cheung, Li C ^a,b   Pan, Qing ^a   Hyun, Noorie ^b   Schiffman, Mark ^b   Fetterman, Barbara ^c   Castle, Philip E ^d   Lorey, Thomas ^c   Katki, Hormuzd A ^b  

^a GEORGE WASHINGTON UNIVERSITY   (United States)

^b NATIONAL CANCER INSTITUTE   (United States)

^c KAISER PERMANENTE   (United States)

^d ALBERT EINSTEIN COLLEGE OF MEDICINE   (United States)

Author keywords

cervical cancer; cumulative risk estimation; HPV; Kaplan Meier; prevalence incidence models

Indexed keywords

ALGORITHM; ARTICLE; CANCER INCIDENCE; CANCER SCREENING; COHORT ANALYSIS; COMPUTER SIMULATION; COVARIANCE; CUMULATIVE SCALE; DIAGNOSTIC ERROR; ELECTRONIC HEALTH RECORD; FEMALE; HEALTH PROGRAM; HUMAN; KAPLAN MEIER METHOD; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; PREVALENCE; STATISTICAL MODEL; UTERINE CERVIX CANCER; ADULT; AGED; CALIFORNIA; COMPARATIVE STUDY; COST BENEFIT ANALYSIS; INCIDENCE; MIDDLE AGED; NONPARAMETRIC TEST; PAPANICOLAOU TEST; SURVIVAL ANALYSIS; UTERINE CERVIX TUMOR;

ADULT; AGED; ALGORITHMS; CALIFORNIA; COHORT STUDIES; COST-BENEFIT ANALYSIS; ELECTRONIC HEALTH RECORDS; FEMALE; HUMANS; INCIDENCE; LOGISTIC MODELS; MIDDLE AGED; PAPANICOLAOU TEST; PREVALENCE; STATISTICS, NONPARAMETRIC; SURVIVAL ANALYSIS; UTERINE CERVICAL NEOPLASMS;

EID: 85021437043     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.7380     Document Type: Article

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