Cost-effectiveness analysis in R using a multi-state modelling survival analysis framework: a tutorial

This tutorial provides a step-by-step guide to performing cost-effectiveness analysis using a multi-state modelling approach. Alongside the tutorial we provide easy-to-use functions in the statistics package R. We argue this multi-state modelling approach using a package such as R has advantages over approaches where models are built in a spreadsheet package. In particular, using a syntax-based approach means there is a written record of what was done and the calculations are transparent. Reproducing the analysis is straightforward as the syntax just needs to be run again. The approach can be thought of as an alternative way to build a Markov decision analytic model, which also has the option to use a state-arrival extended approach if the Markov property does not hold. In the state-arrival extended multi-state model a covariate that represents patients’ history is included allowing the Markov property to be tested. We illustrate the building of multi-state survival models, making predictions from the models and assessing fits. We then proceed to perform a cost-effectiveness analysis including deterministic and probabilistic sensitivity analyses. Finally, we show how to create two common methods of visualising the results, namely cost-effectiveness planes and cost-effectiveness acceptability curves. The analysis is implemented entirely within R. It is based on adaptions to functions in the existing R package mstate, to accommodate parametric multi-state modelling which facilitates extrapolation of survival curves

Briefing: UK Ministry of Defence Force Protection Engineering Programme

The Defence Science and Technology Laboratory sponsored, QinetiQ-led Force Protection Engineering Research Programme has two main strands, applied and underpinning research. The underpinning strand is led by Blastech Ltd. One focus of this research is into the response of geomaterials to threat loading. The programme on locally won fill is split into four main characterisation strands: high-stress (GPa) static pressure–volume; medium-rate pressure–volume (split Hopkinson bar); high-rate (flyer plate) pressure–volume; and unifying modelling research at the University of Sheffield, which has focused on developing a high-quality dataset for locally won fill in low and medium strain rates. With the test apparatus at Sheffield well-controlled tests can be conducted at both high strain rate and pseudo-static rates up to stress levels of 1 GPa. The University of Cambridge has focused on using one-dimensional shock experiments to examine high-rate pressure–volume relationships. Both establishments are examining the effect of moisture content and starting density on emergent rate effects. Blastech Ltd has been undertaking carefully controlled fragment impact experiments, within the dataspace developed by the Universities of Sheffield and Cambridge. The data from experiments are unified by the QinetiQ-led modelling team, to predict material behaviour and to derive a scalable locally won fill model for use in any situation

The Panchromatic Hubble Andromeda Treasury. VI. The reliability of far-ultraviolet flux as a star formation tracer on sub-kpc scales

We have used optical observations of resolved stars from the Panchromatic Hubble Andromeda Treasury (PHAT) to measure the recent (< 500 Myr) star formation histories (SFHs) of 33 FUV-bright regions in M31. The region areas ranged from ~$10^4$ to $10^6$ pc$^2$, which allowed us to test the reliability of FUV flux as a tracer of recent star formation on sub-kpc scales. The star formation rates (SFRs) derived from the extinction-corrected observed FUV fluxes were, on average, consistent with the 100-Myr mean SFRs of the SFHs to within the 1$\sigma$ scatter. Overall, the scatter was larger than the uncertainties in the SFRs and particularly evident among the smallest regions. The scatter was consistent with an even combination of discrete sampling of the initial mass function and high variability in the SFHs. This result demonstrates the importance of satisfying both the full-IMF and the constant-SFR assumptions for obtaining precise SFR estimates from FUV flux. Assuming a robust FUV extinction correction, we estimate that a factor of 2.5 uncertainty can be expected in FUV-based SFRs for regions smaller than $10^5$ pc$^2$, or a few hundred pc. We also examined ages and masses derived from UV flux under the common assumption that the regions are simple stellar populations (SSPs). The SFHs showed that most of the regions are not SSPs, and the age and mass estimates were correspondingly discrepant from the SFHs. For those regions with SSP-like SFHs, we found mean discrepancies of 10 Myr in age and a factor of 3 to 4 in mass. It was not possible to distinguish the SSP-like regions from the others based on integrated FUV flux.Comment: Accepted for publication in The Astrophysical Journa