On the improved estimation of the normal mixture components for longitudinal data.

When analyzing real data sets, statisticians often face the question that the data are heterogeneous and it may not necessarily be possible to model this heterogeneity directly. One natural option in this case is to use the methods based on finite mixtures. The key question in these techniques often is what is the best number of mixtures or, depending on the focus of the analysis, the best number of sub-populations when the model is otherwise fixed.

Computational fluid dynamics (CFD) modelling of liquid embolic agents (Onyx) used in brain arteriovenous malformation (AVM) treatment to predict the distal penetration behavior.

Introduction: Benchtop and animal models have traditionally been used to study the propagation of Onyx Liquid Embolic Systems (Onyx) used in the treatment of brain arteriovenous malformations (AVM). However, such models are costly, do not provide sufficient detail to elucidate how variations in Onyx viscosity alter flow dynamics, and rely on some trial-and-error, resulting in elongated timelines for product development.

Objectives: The goal of this study was to leverage Computational Fluid Dynamics (CFD) simulations to predict the behavior of different Onyx formulations.

Representing subpopulations with latent profile analysis: a non-technical introduction using exercisers' goal orientation adoption profiles.

Latent profile analysis (LPA) is in the finite mixture model analysis family and identifies subgroups by participants' responses to continuous variables (i.e., indicators); participants' probable membership in each subgroup is based on the similarity between the subgroup's prototypical responses and the person's unique responses.

Determining the power of a 1-sided z-test given only the power of the corresponding 2-sided test.

Estimating statistical power is essential for designing behavioral medicine studies efficiently and conserving finite resources. Sometimes behavioral medicine researchers are interested in calculating power for 1-sided z-tests of individual parameters (e.g.

Response to biologics along a gradient of T2 involvement in patients with severe asthma: a data-driven biomarker clustering approach.

Background: Asthma with low levels of T2-biomarkers is poorly understood.

Objective: To characterize severe asthma phenotypes and compare pre- to post-biologic change in asthma outcomes along a gradient of T2-involvement.

Methods: This was a registry-based, cohort study including data from 24 countries.