Statistical Interference Modeling Task
A Statistical Interference Modeling Task is a statistical modeling of overlapping probability distributions.
- Example(s):
- a Treated Subject can influence the outcome of an Untreated Subject (e.g. in vaccines).
- See: Probability Distribution.
References
2016
- (Wikipedia, 2016) ⇒ https://en.wikipedia.org/wiki/statistical_interference Retrieved:2016-9-14.
- When two probability distributions overlap, statistical interference exists. Knowledge of the distributions can be used to determine the likelihood that one parameter exceeds another, and by how much.
This technique can be used for dimensioning of mechanical parts, determining when an applied load exceeds the strength of a structure, and in many other situations. This type of analysis can also be used to estimate the probability of failure or the frequency of failure.
- When two probability distributions overlap, statistical interference exists. Knowledge of the distributions can be used to determine the likelihood that one parameter exceeds another, and by how much.
- https://eng.lyft.com/experimentation-in-a-ridesharing-marketplace-b39db027a66e#.v9yesvcu6
- QUOTE: What happened in the above example is due to a statistical phenomenon known as interference (not to be confused with inference). To properly define it, we first have to introduce the notion of a potential outcome. ...
A key assumption of causal inference is that what’s written on those two pieces of paper is unaffected by the experimental assignment that the unit happens to get, and by the assignments of every other unit in the experiment. Interference occurs when the group assignment of unit A changes any of the potential outcomes of unit B. This is precisely what we saw in the toy example above, with the outcome of interest being whether or not a ride is completed. When user A’s Prime Time is subsidized, user B is less likely to be able to complete a ride (regardless of whether or not user B’s Prime Time is also subsidized).
In medical statistics, the notion of interference arose in the study of vaccines for infectious diseases. The effectiveness of a vaccine on one subject’s outcomes depends on how many others in his social circle also received the immunization. In other words, one subject’s treatment can offer protective benefit to other, possibly untreated subjects. The result is that the measured difference between treated and untreated subjects (the benefit attributed to the vaccine) will shrink. Above, user A’s Prime Time was “protective” for user B’s propensity to successfully complete a Lyft ride — which in this case led to an exaggeration of the true effect size. In general, interference bias can occur in either direction.
- QUOTE: What happened in the above example is due to a statistical phenomenon known as interference (not to be confused with inference). To properly define it, we first have to introduce the notion of a potential outcome. ...
2006
- Flury, Manuel. “Interference mitigation by statistical interference modeling in an impulse radio UWB receiver." In 2006 IEEE International Conference on Ultra-Wideband, pp. 393-398. IEEE, 2006.
- QUOTE: Some impulse radio UWB (IR-UWB) networks may allow concurrent transmissions without power control (for example MAC protocols that do not use power control, or co-existing, non-coordinated piconets). In such cases, it has been proposed to mitigate multi-user interference (MUI) at the physical layer, but existing proposals for interference mitigation do not account for the multipath nature of UWB channels. We address this problem and propose a receiver that employs a combination of statistical interference modeling and thresholding to mitigate MUI.