Inference for social network models from egocentrically sampled data, with application to understanding persistent racial disparities in HIV prevalence in the US

Research article (The Annals of Applied Statistics, 2017) · cited 88× · AI/ML
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Inference for social network models from egocentrically sampled data, with application to understanding persistent racial disparities in HIV prevalence in the US is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Inference for social network models from egocentrically sampled data, with application to understanding persistent racial disparities in HIV prevalence in the US. Retrieved October 17, 2026, from https://4ort.xyz/entity/inference-for-social-network-models-from-egocentrically-sampled-data-with-application-to-understanding-persistent-racial
MLA “Inference for social network models from egocentrically sampled data, with application to understanding persistent racial disparities in HIV prevalence in the US.” 4ort.xyz Knowledge Graph, 4ort.xyz, 17 Oct. 2026, https://4ort.xyz/entity/inference-for-social-network-models-from-egocentrically-sampled-data-with-application-to-understanding-persistent-racial.
BibTeX @misc{4ortxyz_inference-for-social-network-models-from-egocentrically-sampled-data-with-application-to-understanding-persistent-racial_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Inference for social network models from egocentrically sampled data, with application to understanding persistent racial disparities in HIV prevalence in the US}}, year = {2026}, url = {https://4ort.xyz/entity/inference-for-social-network-models-from-egocentrically-sampled-data-with-application-to-understanding-persistent-racial}, note = {Accessed: 2026-10-17}}
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