Multiverse analysis offers a powerful framework to assess the robustness of statistical inferences across a spectrum of plausible analytical choices. However, when applied to predictor selection, especially in high-dimensional settings, the issue of multiplicity becomes critical. In this study, we present a comprehensive simulation framework to evaluate the impact of different multiple testing...
Despite the availability of vaccines, infectious diseases such as COVID-19, tetanus, diphtheria, and pertussis remain persistent public health threats, particularly among vulnerable populations including pregnant and lactating women. As most research on protection against infectious diseases to date has focused on antibody-mediated responses, understanding how antibodies behave over time...
Meta-analysis can be formulated as the combination of p-values from multiple studies into a joint p-value function, from which inference for the average effect, including point estimates and confidence intervals, can be derived. We extend Edgington's p-value combination method for random-effects meta-analysis by treating the combined p-value function as a confidence distribution of the average...
Breast cancer remains one of the most common cancers among women worldwide. Breast cancer screening programmes aim to catch the disease at its early phase, by regularly examining asymptomatic women for signs of cancer. The rationale is straightforward: early detection, before symptoms onset, offers patients broader treatment options and improves the chances of recovery. To evaluate the cancer...
In this study, PERMY data set taken from Pharmaceutical Statistics Using SAS: A Practical Guide is analyzed. It describes permeability of cell membranes, which is the ability of a molecule to cross a membrane. Biological structures are a complex layer of molecules and proteins. Substances require a particular structure to pass through the target membrane and drugs that fail to demonstrate...
