Simulation studies are widely used for evaluating the performance of statistical methods in
psychology. However, the quality of simulation studies can vary widely in terms of their …

Simulation studies are essential tools to assess statistical methods. Functioning as
controlled experiments, simulations generate data from known underlying processes …

Introduction Non-compliance is a common challenge for researchers and may reduce the
power of an intention-to-treat analysis. Whilst a per protocol approach attempts to deal with …

We warn against a common but incomplete understanding of empirical research in machine
learning that leads to non-replicable results, makes findings unreliable, and threatens to …

The constant development of new data analysis methods in many fields of research is
accompanied by an increasing awareness that these new methods often perform better in …

BACKGROUND: Patients with acute hypoxemic respiratory failure are at high risk of death
and prolonged time on the ventilator. Interventions often aim to reduce both mortality and …

Simulation studies are commonly used in methodological research for the empirical
evaluation of data analysis methods. They generate artificial data sets under specified …

Researchers often perform data-driven variable selection when modeling the associations
between an outcome and multiple independent variables in regression analysis. Variable …

Monte Carlo simulation studies are among the primary scientific outputs contributed by
methodologists, guiding application of various statistical tools in practice. Although …

Due to the abundance of single cell RNA-seq data, a number of methods for predicting
expression after perturbation have recently been published. Expression prediction methods …