Length-biased data analysis and survival modeling have become pivotal in accurately interpreting time-to-event data, particularly in epidemiology and clinical research. Traditional survival analyses ...

Discover how sample size neglect impacts statistical conclusions and learn to avoid this cognitive bias studied by renowned experts like Tversky and Kahneman.

Aim Although data collected by citizen scientists have received a great deal of attention for assessing species distributions over large extents, their sampling efforts are usually spatially biased.

Biased sampling occurs frequently in economics, epidemiology, and medical studies either by design or due to data collecting mechanism. Failing to take into account the sampling bias usually leads to ...

Ravishankar, Pavan, Qingyu Mo, Edward McFowland III, and Daniel B. Neill. "Provable Detection of Propagating Sampling Bias in Prediction Models." Proceedings of the AAAI Conference on Artificial ...

In this special guest feature, Sinan Ozdemir, Director of Data Science at Directly, points out how algorithmic bias has been one of the most talked-about issues in AI for years, yet it remains one of ...

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Systematic sampling is straightforward and low risk, offering better control. However, it may introduce sampling errors and ...

Recently, an Association Workforce Monitor online survey conducted by the Harris Poll asked over 2,000 U.S. adults their thoughts on AI recruiting tools. About one-third of respondents in this recent ...