title: Power and sample size calculations for interval-censored survival analysis.
abstract: We propose a method for calculating power and sample size for studies involving interval-censored failure time data that only involves standard software required for fitting the appropriate parametric survival model. We use the framework of a longitudinal study where patients are assessed periodically for a response and the only resultant information available to the investigators is the failure window: the time between the last negative and first positive test results. The survival model is fit to an expanded data set using easily computed weights. We illustrate with a Weibull survival model and a two-group comparison. The investigator can specify a group difference in terms of a hazards ratio. Our simulation results demonstrate the merits of these proposed power calculations. We also explore how the number of assessments (visits), and thus the corresponding lengths of the failure intervals, affect study power. The proposed method can be easily extended to more complex study designs and a variety of survival and censoring distributions.
authors.affiliation: Department of Epidemiology and Community Health, New York Medical College, 40 Sunshine Cottage Rd, Valhalla, NY 10595, U.S.A.
authors.forename: Hae-Young
authors.initials: HY
authors.lastname: Kim
authors.affiliation: Division of Parasitic Diseases and Malaria, National Center of Global Health, Centers for Disease Control and Prevention (MS A-06), 1600 Clifton Road, Atlanta, GA 30329, U.S.A.
authors.forename: John M
authors.initials: JM
authors.lastname: Williamson
authors.affiliation: Department of Population Health Science and Policy, Ichan School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, Box 1010, NY 10029, U.S.A.
authors.forename: Hung-Mo
authors.initials: HM
authors.lastname: Lin
mesh_terms: D056808:Biostatistics; D001943:Breast Neoplasms / Q000628:therapy; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D016016:Proportional Hazards Models; D012044:Regression Analysis; D018401:Sample Size; D016019:Survival Analysis; D013997:Time Factors
keywords: interval-censored data; parametric survival analysis; power; sample size