Bayesian Analysis of the Polarization of Distant Radio Sources: Limits on Cosmological Birefringence

A recent study of the rotation of the plane of polarization of light from 160 cosmological sources claims to find significant evidence for cosmological anisotropy. We point out methodological weaknesses of that study, and reanalyze the same data using Bayesian methods that overcome these problems. We find that the data always favor isotropic models for the distribution of observed polarizations over counterparts that have a cosmological anisotropy of the type advocated in the earlier study. Although anisotropic models are not completely ruled out, the data put strong lower limits on the length scale $\lambda$ (in units of the Hubble length) associated with the anisotropy; the lower limits of 95% credible regions for $\lambda$ lie between 0.43 and 0.62 in all anisotropic models we studied, values several times larger than the best-fit value of $\lambda \approx 0.1$ found in the earlier study. The length scale is not constrained from above. The vast majority of sources in the data are at distances closer than 0.4 Hubble lengths (corresponding to a redshift of $\approx$0.8); the results are thus consistent with there being no significant anisotropy on the length scale probed by these data.Comment: 8 pages, 3 figures; submitted to Phys. Rev.

What Have We Learned about Trial Design From NIMH-Funded Pragmatic Trials?

At the 2008 annual meeting of the American College of Neuropsychopharmacology (ACNP), a symposium was devoted to the following question: ‘what have we learned about the design of pragmatic clinical trials (PCTs) from the recent costly long-term, large-scale trials of psychiatric treatments?' in order to inform the design of future trials. In all, 10 recommendations were generated placing emphasis on (1) appropriate conduct of pragmatic trials; (2) clinical, rather than, merely statistical significance; (3) sampling from the population clinicians are called upon to treat; (4) clinical outcomes of patients, rather than, on outcome measures; (5) use of stratification, controlling, or adjusting when necessary and not otherwise; (6) appropriate consideration of site differences in multisite studies; (7) encouragement of ‘post hoc' exploration to generate (not test) hypotheses; (8) precise articulation of the treatment strategy to be tested and use of the corresponding appropriate design; (9) expanded opportunity for training of researchers and reviewers in RCT principles; and (10) greater emphasis on data sharing