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Effect Inference From Two-Group Data With Sampling Bias
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.ORCID iD: 0000-0002-6698-0166
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.ORCID iD: 0000-0002-7957-3711
2019 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 26, no 8, p. 1103-1106Article in journal (Refereed) Published
Abstract [en]

In many applications, different populations are compared using data that are sampled in a biased manner. Under sampling biases, standard methods that estimate the difference between the population means yield unreliable inferences. Here, we develop an inference method that is resilient to sampling biases and is able to control the false positive errors under moderate bias levels in contrast to the standard approach. We demonstrate the method using synthetic and real biomarker data.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2019. Vol. 26, no 8, p. 1103-1106
Keywords [en]
Sampling bias, statistical inference, two-sample test
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-390076DOI: 10.1109/LSP.2019.2921255ISI: 000472209500002OAI: oai:DiVA.org:uu-390076DiVA, id: diva2:1340880
Funder
Swedish Research Council, 2018-05040Available from: 2019-08-06 Created: 2019-08-06 Last updated: 2019-08-06Bibliographically approved

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Zachariah, DaveStoica, Petre

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