In basic neuroscience research, data are often clustered or collected with repeated
measures, hence correlated. The most widely used methods such as t test and ANOVA do …

Markov chain Monte Carlo (MCMC) is one of the most useful approaches to scientific
computing because of its flexible construction, ease of use, and generality. Indeed, MCMC is …

We present the results of the search for an isotropic stochastic gravitational wave
background (GWB) at nanohertz frequencies using the second data release of the European …

Abstract The paper introduces Bayesian Mindsponge Framework (BMF) analytics, a new
analytical tool for investigating socio, psychological, and behavioral phenomena. The …

Natural light cycles are being eroded over large areas of the globe by the direct emissions
and sky brightening that result from sources of artificial night-time light. This is predicted to …

Count data can be analyzed using generalized linear mixed models when observations are
correlated in ways that require random effects. However, count data are often zero-inflated …

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic
complications. Through trans-ancestry meta-analysis of genome-wide association studies of …

The progression of chronic liver disease to hepatocellular carcinoma is caused by the
acquisition of somatic mutations that affect 20–30 cancer genes,,,,,,–. Burdens of somatic …

Climate change could increase species' extinction risk as temperatures and precipitation
begin to exceed species' historically observed tolerances. Using long-term data for 66 …

An organism's ability to disperse influences many fundamental processes, from speciation
and geographical range expansion to community assembly. However, the patterns and …