We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and sample size much more directly than significance testing does; but none of the statistical tools should be taken as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple independent studies. When evaluating the strength of the evidence, we should consider, for example, auxiliary assumptions, the strength of the experimental design, and implications for applications. To boil all this down to a binary decision based on a p-value threshold of 0.05, 0.01, 0.005, or anything else, is not acceptable.

In this paper we are interested in empirical likelihood (EL) as a method of estimation, and we address the following two problems: (1) selecting among various empirical discrepancies in an EL framework and (2) demonstrating that EL has a well-defined probabilistic interpretation that would justify its use in a Bayesian context. Using the large deviations approach, a Bayesian law of large numbers is developed that implies that EL and the Bayesian maximum a posteriori probability (MAP) estimators are consistent under misspecification and that EL can be viewed as an asymptotic form of MAP. Estimators based on other empirical discrepancies are, in general, inconsistent under misspecification.

Congenital fibrinogen disorders are diseases associated with a bleeding tendency; however, there are also reports of thrombotic events. Fibrinogen plays a role in the pathogenesis of thrombosis due to altered plasma concentrations or modifications to fibrinogen’s structural properties, which affect clot permeability, resistance to lysis, and its stiffness. Several distinct types of genetic change and pathogenetic mechanism have been described in patients with bleeding and a thrombotic phenotype, including mutations affecting synthesis or processing in three fibrinogen genes. In this paper, we focused on familial hypofibrinogenemia, a rare inherited quantitative fibrinogen disorder characterized by decreased fibrinogen levels with a high phenotypic heterogeneity. To begin, we briefly review the basic information regarding fibrinogen’s structure, its function, and the clinical consequences of low fibrinogen levels. Thereafter, we introduce 15 case reports with various gene mutations derived from the fibrinogen mutation database GFHT (French Study Group on Hemostasis and Thrombosis), which are associated with congenital hypofibrinogenemia with both bleeding and thrombosis. Predicting clinical presentations based on genotype data is difficult. Genotype–phenotype correlations would be of help to better understand the pathologic properties of this rare disease and to provide a valuable tool for the identification of patients who are not only at risk of bleeding, but also at risk of a thrombotic event.