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Title: Existence and uniqueness of relative incidence estimates in case-series analysis
Authors: Li, Baibing
Huang, Xiangning
Keywords: Case-series analysis
Existence and uniqueness
Maximum likelihood estimate
Nonlinear programming
Relative incidence
Issue Date: 2006
Publisher: © Elsevier
Citation: LI, B. and HUANG, X., 2006. Existence and uniqueness of relative incidence estimates in case-series analysis. Computational Statistics and Data Analysis, 50 (7), pp. 1807-1817.
Abstract: Case-series analysis is used to estimate relative incidences of clinical events in defined time intervals after vaccination compared to a control period. It has advantages, in terms of both a reduction in data collection effort, because it uses only data on cases, and a reduction in the resultant variances of estimates, due to individuals being self-controlled. The existence and uniqueness of relative incidence estimates in case-series analysis are investigated. For the relative incidence of a clinical event, a simple condition for existence and uniqueness of the estimate of the parameter vector in a case-series model is established. An algorithm is developed to examine the established condition, which provides a clue for remedy when the condition for existence and uniqueness is not satisfied.
Description: This article was published in the journal, Computational Statistics and Data Analysis [© Elsevier]. The definitive version is available from: http://www.sciencedirect.com/science/article/pii/S0167947305000319
Version: Accepted for publication
DOI: 10.1016/j.csda.2005.02.002
URI: https://dspace.lboro.ac.uk/2134/9158
Publisher Link: http://www.sciencedirect.com/science/article/pii/S0167947305000319
ISSN: 0167-9473
Appears in Collections:Published Articles (Business School)

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