arXiv subjects

Chris Barker

Publications and source records attributed to Chris Barker.

3 recordsLinked to original sources

arXiv2023

Pragmatic Estimation of Sample Size for Number of Interviews for PRO development in the 2009 FDA PRO guidance

PROs developed de novo, using the FDA guidance may involve structured patient interviews or focus groups. Qualitative Research is a methodology for eliciting and coding interviews and produces concepts or themes. These concepts are used to develop items in a PRO for use as an endpoint in Clinical trials. A convention in the field is that interviews and code/concept elicitation are considered complete when subsequent interviews produces "no new concepts" -termed "saturation". FDA reviewers frequently challenge PRO developers whether there are sufficient patient interviews to confirm that saturation is achieved after occurrence of zero new concepts. Several authors have reported that concrete criteria are need for confirming that saturation is achieved (Francis 2010, Mason 2010, Marshall 2013). I provide statistical methodology for confirming saturation, suitable for review by a regulatory authority. Type I error for saturation, may occur if further interviews elicited more concepts after first occurrence of saturation. I use published data set on code elicitation (Guest, 2006) to demonstrate that saturation may occur more than once in a sequence of interviews. I provide a statistical definition for saturation in qualitative research, that addresses regulatory concerns for PRO's developed for use as a clinical trial endpoint in a regulatory submission.

stat.ME↗

arXiv2021

Horizontal transport in oil-spill modeling

Simulating oil transport in the ocean can be done successfully provided that accurate ocean currents and surface winds are available -- this is often too big of a challenge. Deficient ocean currents can sometimes be remediated by parameterizing missing physics -- this is often not enough. In this chapter, we focus on some of the main problems oil-spill modelers face, which is determining accurate trajectories when the velocity may be missing important physics, or when the velocity has localized errors that result in large trajectory errors. A foundation of physical mechanisms driving motion in the ocean may help identify currents lacking certain types of physics, and the remedy. Recent progress in our understanding of motion in the upper centimeters of the ocean supports unconventional parameterizations; we present as an example the 2003 Point Wells oil spill which had remained unexplained until recently. When the velocity realistically represents trajectory forcing mechanisms, advanced Lagrangian techniques that build on the theory of Lagrangian Coherent Structures can bypass localized velocity errors by identifying regions of attraction likely to dictate fluid deformation. The usefulness of Objective Eulerian Coherent Structures is demonstrated to the oil-spill modeling community by revisiting the 2010 Deepwater Horizon accident in the Gulf of Mexico and predicting a prominent transport pattern from an imperfect altimetry velocity eight days in advance.

physics.ao-ph↗

arXiv2020

Vertical mixing in oil spill modelling

The main focus of marine oil spill modelling is often on where the oil will end up, i.e., on the horizontal transport. However, due to current shear, wind drag, and the different physical, chemical and biological processes that affect oil differently on the surface and in the water column, modelling the vertical distribution of the oil is essential for modelling the horizontal transport. In this work, we review and present models for a number of physical processes that influence the vertical transport of oil, including wave entrainment, droplet rise, vertical turbulent mixing, and surfacing. We aim to provide enough detail for the reader to be able to understand and implement the models, and to provide references to further reading. Mathematical and numerical details are included, particularly on the advection and diffusion of particles. We also present and discuss some common numerical pitfalls that may be a bit subtle, but which can cause significant errors.

physics.ao-ph↗