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Analysis of interval‐censored data from circular migrant and non‐migrant sexual partnerships using the EM algorithm by K. Zuma; M. Lurie; M. Jorgensen is a Mathematics article available to read on EtoBox.

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## Abstract In epidemiological studies where subjects are seen periodically on follow‐up visits, interval‐censored data occur naturally. The exact time the change of state (such as HIV seroconversion) occurs is not known exactly, only that it occurred sometime within a specific time interval. Methods of estimation for interval‐censored data are readily available when data are independent. However, methods for correlated interval‐censored data are not well developed. This paper considers an approach for estimating the parameters when data are interval‐censored and correlated within sexual partnerships. We consider the exact event times for interval‐censored observations as unobserved data, only known to be between two time points. Dependency induced by sexual partnerships is modelled as frailties assuming a gamma distribution for frailties and an exponential distribution on the time to infection. This formulation facilitates application of the expectation‐maximization (EM) algorithm. Maximization process maximizes the standard survival frailty model. Results show high degree of heterogeneity between sexual partnerships. Intervention strategies aimed at combating the spread of HIV an

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Author

K. Zuma; M. Lurie; M. Jorgensen

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0277-6715)

Published

2006

Language

EN

Field

Mathematics (Physical Sciences)