Bias and response heterogeneity in an air quality data set
S. Stanley Young; Robert L. Obenchain; Christophe Lambert · 2015 · arXiv
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
It is well-known that claims coming from observational studies often fail to replicate when rigorously re-tested. The technical problems include multiple testing, multiple modeling and bias. Any or all of these problems can give rise to claims that will fail to replicate. There is a need for statistical methods that are easily applied, are easy to understand, and are likely to give reliable results. In particular, simple ways for reducing the influence of bias are essential. In this paper, the Local Control method developed by Robert Obenchain is explicated using a small air quality/longevity
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Metadata source: arXiv