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Challenges of anonymizing or simulating sensitive time-to-event data on HIV-positive adolescents' sexual behavior

Authors: Smekens, Tom;

Challenges of anonymizing or simulating sensitive time-to-event data on HIV-positive adolescents' sexual behavior

Abstract

{"references": ["Bakeera-Kitaka, S., Smekens, T., Jespers, V., Wobudeya, E., Loos, J., Colebunders, R., Adipo, D., Kekitiinwa, A., Musoke, P., Buve, A., & N\u00f6stlinger, C. (2019). Factors Influencing the Risk of Becoming Sexually Active Among HIV Infected Adolescents in Kampala and Kisumu, East Africa. AIDS and Behavior, 23(6), Article 6. https://doi.org/10.1007/s10461-018-2323-y", "Brilleman, S. L., Wolfe, R., Moreno-Betancur, M., & Crowther, M. J. (2021). Simulating Survival Data Using the simsurv R Package. Journal of Statistical Software, 97, 1\u201327. https://doi.org/10.18637/jss.v097.i03", "DeBruine, L. (2023). faux: Simulation for Factorial Designs. Zenodo. https://doi.org/10.5281/zenodo.2669586", "Jackson, C. (2016). flexsurv: A Platform for Parametric Survival Modeling in R. Journal of Statistical Software, 70, 1\u201333. https://doi.org/10.18637/jss.v070.i08", "Smekens, T. (2022). When retrospective data is censored data. RPubs. http://rpubs.com/tsmekens/alhiv", "Sweeney, L. (2002). K-Anonymity: A Model for Protecting Privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(05), 557\u2013570. https://doi.org/10.1142/S0218488502001648", "Templ, M., Kowarik, A., & Meindl, B. (2015). Statistical Disclosure Control for Micro-Data Using the R Package sdcMicro. Journal of Statistical Software, 67, 1\u201336. https://doi.org/10.18637/jss.v067.i04", "Templ, M. (2017). Statistical Disclosure Control for Microdata. Springer. https://doi.org/10.1007/978-3-319-50272-4"]}

A reflection on challenges encountered when trying to anonymize or simulate time-to-event data on sexual behavior of HIV-positive adolescents, intended as supporting material for an open access vignette on the statistical reasoning behind one paper using such data. The extremely sensitive nature of the data, combined with the technique's data requirements, make either approach exceptionally challenging.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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