arXiv subjects

Emily K. Roberts

Publications and source records attributed to Emily K. Roberts.

4 recordsLinked to original sources

arXiv2025

Assessing the star formation history of all-sky and part-sky 100pc white dwarf samples

Thanks to Gaia and large-scale spectroscopic follow-up surveys (4MOST, DESI, WEAVE, SDSS-V), it is now possible to build representative and minimally biased samples of the local white dwarf population. Here we analyse several volume-limited 100pc samples of white dwarfs, constructed from different surveys and studies, to evaluate their completeness and residual biases. We model the underlying star formation history and Galactic disc age via comparison with simulated populations of white dwarfs to quantitatively characterise completeness. We assess whether the benefit of Gaia XP spectra in datasets outweighs the reduction in sample size, and to what extent targeted, part-sky, and magnitude limited surveys can be used in comparison to all-sky volume limited surveys. Additionally, we simulate the 4MOST 100PC sub-survey and discuss its use to better understand the local star formation history.

astro-ph.SR↗

arXiv2025

What's the Weight? Estimating Controlled Outcome Differences in Complex Surveys for Health Disparities Research

In this work, we are motivated by the problem of estimating racial disparities in health outcomes, specifically the average controlled difference (ACD) in telomere length between Black and White individuals, using data from the National Health and Nutrition Examination Survey (NHANES). To do so, we build a propensity for race to properly adjust for other social determinants while characterizing the controlled effect of race on telomere length. Propensity score methods are broadly employed with observational data as a tool to achieve covariate balance, but how to implement them in complex surveys is less studied - in particular, when the survey weights depend on the group variable under comparison (as the NHANES sampling scheme depends on self-reported race). We propose identification formulas to properly estimate the ACD in outcomes between Black and White individuals, with appropriate weighting for both covariate imbalance across the two racial groups and generalizability. Via extensive simulation, we show that our proposed methods outperform traditional analytic approaches in terms of bias, mean squared error, and coverage when estimating the ACD for our setting of interest. In our data, we find that evidence of racial differences in telomere length between Black and White individuals attenuates after accounting for confounding by socioeconomic factors and utilizing appropriate propensity score and survey weighting techniques. Software to implement these methods and code to reproduce our results can be found in the R package svycdiff, available through the Comprehensive R Archive Network (CRAN) at cran.r-project.org/web/packages/svycdiff/, or in a development version on GitHub at github.com/salernos/svycdiff.

stat.ME↗

arXiv2025

Comparison of methods used to derive the Galactic star formation history from white dwarf samples

We compare three methods of deriving the local Galactic star formation history, using as a benchmark the Gaia-defined 40 pc white dwarf sample, currently the largest volume complete sample of stellar remnants with medium-resolution spectroscopy. We create a population synthesis model to 1) reproduce the observed white dwarf luminosity function, 2) reproduce the observed absolute Gaia G magnitude distribution, and 3) directly calculate the ages of all individual white dwarfs in the 40 pc volume. We then compare the star formation histories determined from each method. Previous studies using these methods were based on different white dwarf samples and as such were difficult to compare. Uncertainties in each method such as the initial mass function, initial-final mass relation, main sequence lifetimes, stellar metallicity, white dwarf cooling ages and binary evolution are accounted for to estimate the precision and accuracy of each method. We conclude that no method is quantitatively better at determining the star formation history and all three produce star formation histories that agree within uncertainties of current external astrophysical relations.

astro-ph.SR↗

arXiv2022

Surrogacy Validation for Time-to-Event Outcomes with Illness-Death Frailty Models

A common practice in clinical trials is to evaluate a treatment effect on an intermediate endpoint when the true outcome of interest would be difficult or costly to measure. We consider how to validate intermediate endpoints in a causally-valid way when the trial outcomes are time-to-event. Using counterfactual outcomes, those that would be observed if the counterfactual treatment had been given, the causal association paradigm assesses the relationship of the treatment effect on the surrogate $S$ with the treatment effect on the true endpoint $T$. In particular, we propose illness death models to accommodate the censored and semi-competing risk structure of survival data. The proposed causal version of these models involves estimable and counterfactual frailty terms. Via these multi-state models, we characterize what a valid surrogate would look like using a causal effect predictiveness plot. We evaluate the estimation properties of a Bayesian method using Markov Chain Monte Carlo and assess the sensitivity of our model assumptions. Our motivating data source is a localized prostate cancer clinical trial where the two survival endpoints are time to distant metastasis and time to death.

stat.ME↗