Explaining Counts from EPRB Experiments: Are They Consistent with   Quantum Theory?
  I have fit data from EPRB experiments of Weihs et al to a model that consists of an EPRB thought experiment whose output is filtered. The filter implements the assumptions made by most investigators: that EPRB experiments satisfy a fair sampling assumption; and that detections and coincidences occur randomly with Poisson distributions (this provides a basis for calculating standard errors of coincidence counts, correlations, and so forth). The model does not fit the data-predicted and observed counts of detections and coincidences differ far too much, by a chi-square criterion. Logically, one must give up fair sampling and/or Poisson errors and/or the assumption that the data derive ultimately from an EPRB thought experiment. In the literature, giving up fair sampling seems to be coupled to giving up EPRB, but to me it seems just as sensible to keep EPRB and to give up fair sampling and Poisson errors. Some rather ordinary mechanisms can violate fair sampling, and there is the possibility in any experiment for uncontrolled and unmonitored factors to contribute to unwanted variation. By sufficiently relaxing the fair sampling and Poisson assumptions-it doesn't take much-my model can be made to fit the data. 
James H. Bigelow
quant-ph