3 citations · 3 across the 3 of their papers we have counts for
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stat.AP2023
Commentary on Guyll et al. (2023): Misuse of Statistical Method Results in Highly Biased Interpretation of Forensic Evidence
Michael Rosenblum, Elizabeth T. Chin, Elizabeth L. Ogburn +6
Since the National Academy of Sciences released their report outlining paths for improving reliability, standards, and policies in the forensic sciences NAS (2009), there has been…
stat.AP2019
Network Dependence Can Lead to Spurious Associations and Invalid Inference
Youjin Lee, Elizabeth L. Ogburn
Researchers across the health and social sciences generally assume that observations are independent, even while relying on convenience samples that draw subjects from one or a sma…
stat.AP2017
Challenges to estimating contagion effects from observational data
Elizabeth L. Ogburn
A growing body of literature attempts to learn about contagion using observational (i.e. non-experimental) data collected from a single social network. While the conclusions of the…