•  2
    Sometimes Size Does Not Matter
    with Robert J. Marks and Daniel Andrés Díaz-Pachón
    Foundations of Physics 53 (1): 1-29. 2022.
    AbstractRecently Díaz, Hössjer and Marks presented a Bayesian framework to measure cosmological tuning that uses maximum entropy distributions on unbounded sample spaces as priors for the parameters of the physical models. The DHM framework stands in contrast to previous attempts to measure tuning that rely on a uniform prior assumption. However, since the parameters of the models often take values in spaces of infinite size, the uniformity assumption is unwarranted. This is known as the normali…Read more
  •  3
    Novel bounds for causal effects based on sensitivity parameters on the risk difference scale
    with Arvid Sjölander
    Journal of Causal Inference 9 (1): 190-210. 2021.
    Unmeasured confounding is an important threat to the validity of observational studies. A common way to deal with unmeasured confounding is to compute bounds for the causal effect of interest, that is, a range of values that is guaranteed to include the true effect, given the observed data. Recently, bounds have been proposed that are based on sensitivity parameters, which quantify the degree of unmeasured confounding on the risk ratio scale. These bounds can be used to compute an E-value, that …Read more