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Obesity rates have been increasing over recent decades, causing significant concern among policy makers. Excess body fat, commonly measured by body mass index (BMI), is a major risk factor for several common disorders including diabetes and…
The Classical Twin Paradox is widely dealt in literature and neatly resolved. In addition, it is also well known that, when looking at two systems which are boosted relative to each other, the concept of the simultaneous effect of a quantum…
Aggregated health data such as claims data from health insurances become more and more available for research purposes. Estimates of excess mortality from prevalence and incidence of a chronic condition have only been possible for ages 50…
Observational studies of causal effects require adjustment for confounding factors. In the tabular setting, where these factors are well-defined, separate random variables, the effect of confounding is well understood. However, in public…
Unmeasured confounding is a key challenge for causal inference. In this paper, we establish a framework for unmeasured confounding adjustment with negative control variables. A negative control outcome is associated with the confounder but…
The case that the factor model does not account for all the covariances of the observed variables is considered. This is a quite realistic condition because some model error as well as some sampling error should usually occur with empirical…
Twins travelling at constant relative velocity will each see the other's time dilate leading to the apparent paradox that each twin believes the other ages more slowly. In a finite space, the twins can both be on inertial, periodic orbits…
The well-known Simpson's Paradox, or Yule-Simpson Effect, in statistics is often illustrated by the following thought experiment: A drug may be found in a trial to increase the survival rate for both men and women, but decrease the rate for…
It is now increasingly realized that the underlying mechanism which governs aging (ageing) is a complex interplay of genetic regulation and damage-accumulation. "Aging as a result of accumulation of 'faults' on cellular and molecular…
Chronic diseases such as diabetes are quite prevalent in the world and are responsible for a significant number of deaths per year. In addition, treatments for such chronic diseases account for a high healthcare cost. However, research has…
Understanding the relationship between population dynamics and disease-specific mortality is central to evidence-based health policy. This study introduces two novel metrics, PoPDivergence and PoPStat, one to quantify the difference between…
Propensity Score Matching (PSM) stands as a widely embraced method in comparative effectiveness research. PSM crafts matched datasets, mimicking some attributes of randomized designs, from observational data. In a valid PSM design where all…
There are many measures to report so-called treatment or causal effects: absolute difference, ratio, odds ratio, number needed to treat, and so on. The choice of a measure, e.g. absolute versus relative, is often debated because it leads to…
Quantum three box paradox is a prototypical example of some bizarre predictions for intermediate measurements made on pre- and post-selected systems. Although in principle those effects can be explained by measurement disturbance, it is not…
Currently emerging "big data" techniques are reshaping medical science into a data science. Medical claims data allow assessing an entire nation's health state in a quantitative way, in particular with regard to the occurrences and…
After pointing out the historical avatar at the origin of a would be twin or clock paradox, we argue that, at least on a local scale, the (re-qualified) paradox is but a necessary consequence of the sole principle of causality.
Among the most impactful diabetic complications are diabetic retinopathy, the leading cause of blindness among working class adults, and cardiovascular disease, the leading cause of death worldwide. This study describes the development of…
The advent of molecular biology has led to the identification of definitive causative factors for a number of diseases, most of which are monogenic. Causes for most common diseases across the population, however, seem elusive and cannot be…
We propose a novel framework for conducting causal inference based on counterfactual densities. While the current paradigm of causal inference is mostly focused on estimating average treatment effects (ATEs), which restricts the analysis to…
This paper describes Simpson's paradox, and explains its serious implications for randomised control trials. In particular, we show that for any number of variables we can simulate the result of a controlled trial which uniformly points to…