Clinical trials play a decisive role in the drug approval processes. By completing a p-curve analysis of a newly compiled data set that consists of thousands of clinical trials, we substantiate that the occurrence of p-hacking in clinical trials is not merely hypothetical. Medical and...

Although we did not find any statistical significant differences in health care costs, we did observe a higher consumption of prescribed medication and lower costs of work hours lost if both patient and GPs participated in a former clinical trial. The results may be limited due to a lower number...

Ranked set sampling (RSS) is a technique for incorporating auxiliary (concomitant) information into estimation and testing procedures right at the design stage. In this paper, we propose group sequential testing procedures for comparing two treatments with binary outcomes under an RSS scheme...

In this article we consider the sample size determination problem in the context of robust Bayesian parameter estimation of the Bernoulli model. Following a robust approach, we consider classes of conjugate Beta prior distributions for the unknown parameter. We assume that inference is robust if...

Experimental design represents the typical context in which the interplay between Bayesian and frequentist methodology is natural and useful. Before the data are observed, it is licit and unavoidable even for a Bayesian statistician to take into account sample variability for the evaluation of...

The accounts of medical trials provide very detailed information about the patients’ health conditions. On the contrary, almost no vital data such as marital status or age distribution are usually given. Yet, some of these factors can have a notable impact on the overall death rate, thereby...

Literature claims for a deeper understanding of which processes shape the evolution of network structures over time. Drawing on the assumption that the “normative ideal” network structure should be understood according to the context in which the network is embedded, we observe collaborative...