Related papers: Examining socioeconomic health disparities using a…
Background: As value-based care expands across the U.S. healthcare system, reducing health disparities has become a priority. Social determinants of health (SDoH) indices, like the widely used Area Deprivation Index (ADI), guide efforts to…
Many existing fairness metrics measure group-wise demographic disparities in system behavior or model performance. Calculating these metrics requires access to demographic information, which, in industrial settings, is often unavailable. By…
Socioeconomic integration is a critical dimension of social equity, yet persistent disparities remain in access to health insurance, education, and employment across different demographic groups. While previous studies have examined…
Assessing research that pushes the boundaries of knowledge is challenging because such work is extremely infrequent, accounting for only about 0.01 per cent of all research outputs. Consequently, knowledge about how to evaluate this type of…
Matching is a popular nonparametric covariate adjustment strategy in empirical health services research. Matching helps construct two groups comparable in many baseline covariates but different in some key aspects under investigation. In…
Open challenges have become the de facto standard for comparative ranking of medical AI methods. Despite their importance, medical AI leaderboards exhibit three persistent limitations: (1) score gaps are rarely tested for statistical…
Background: A wide range of diseases show some degree of clustering in families; family history is therefore an important aspect for clinicians when making risk predictions. Familial aggregation is often quantified in terms of a familial…
Healthcare quality metrics refer to a variety of measures used to characterize what should have been done or not done for a patient or the health consequences of what was or was not done. When estimating healthcare quality, many metrics are…
Social inequality is traditionally measured by the Gini-index ($g$). The $g$-index takes values from $0$ to $1$ where $g=0$ represents complete equality and $g=1$ represents complete inequality. Most of the estimates of the income or wealth…
The continuous net reclassification improvement (NRI) statistic is a popular model change measure that was developed to assess the incremental value of new factors in a risk prediction model. Two prominent statistical issues identified in…
The pursuit of having an appropriate level of income inequality should be viewed as one of the biggest challenges facing academic scholars as well as policy makers. Unfortunately, research on this issue is currently lacking. This study is…
Improving health worldwide will require rigorous quantification of population-level trends in health status. However, global-level surveys are not available, forcing researchers to rely on fragmentary country-specific data of varying…
This dissertation is based on a project co-founded by the Health Market Quality Program (now Rozetta Institute) and the Australian Institute of Health and Welfare. The overall objective of this work is to provide a framework and a tool for…
We study a rank based univariate two-sample distribution-free test. The test statistic is the difference between the average of between-group rank distances and the average of within-group rank distances. This test statistic is closely…
The Rural Access Index (RAI), one of the UN Sustainable Development Goal indicators (SDG 9.1.1), represents the proportion of the rural population residing within 2 km of all-season roads. It reflects the accessibility of rural residents to…
Differences in data distributions between demographic groups, known as the problem of infra-marginality, complicate how people evaluate fairness in machine learning models. We present a user study with 85 participants in a hypothetical…
The Adjusted Rand Index ($ARI$) is arguably one of the most popular measures for cluster comparison. The adjustment of the $ARI$ is based on a hypergeometric distribution assumption which is unsatisfying from a modeling perspective as (i)…
Effect size indices are useful parameters that quantify the strength of association and are unaffected by sample size. There are many available effect size parameters and estimators, but it is difficult to compare effect sizes across…
During the COVID-19 pandemic, we witnessed a disproportionate infection rate among marginalized and low-income groups. Despite empirical evidence suggesting that structural inequalities in society contribute to health disparities, there has…
Ranking pertaining to the human-centered tasks -- underscoring their paramount significance in these domains such as evaluation and hiring process -- exhibits widespread prevalence across various industries. Consequently, decision-makers…