title: A maximum Likelihood Approach to Analyzing Incomplete Longitudinal Data in Mammary Tumor Development Experiments with Mice.
abstract: Longitudinal mammary tumor development studies using mice as experimental units are affected by i) missing data towards the end of the study by natural death or euthanasia, and ii) the presence of censored data caused by the detection limits of instrumental sensitivity. To accommodate these characteristics, we investigate a test to carry out K-group comparisons based on maximum likelihood methodology. We derive a relevant likelihood ratio test based on general distributions, investigate its properties of based on theoretical propositions, and evaluate the performance of the test via a simulation study. We apply the results to data extracted from a study designed to investigate the development of breast cancer in mice.
authors.affiliation: Department of Biostatistics, University at Buffalo, the State University of New York, NY 14214, U.S.A.
authors.forename: Jihnhee
authors.initials: J
authors.lastname: Yu
authors.affiliation: Department of Biostatistics, University at Buffalo, the State University of New York, NY 14214, U.S.A.
authors.forename: Albert
authors.initials: A
authors.lastname: Vexler
authors.affiliation: Department of Biostatistics, University at Buffalo, the State University of New York, NY 14214, U.S.A.
authors.forename: Alan D
authors.initials: AD
authors.lastname: Hutson
keywords: Incomplete data; K-group comparison; Limit of detection; Mammary tumor development; Missing data