Abstract In studies of clinical phenotypes, such as dementia, disability, and frailty, participants are typically assessed at in-person clinic visits. Thus, the precise time of onset for the phenotype is unknown. The discreteness of the clinic visits yields grouped event time data. We...

Abstract Instrumental variables is a popular method in epidemiology and related fields, to estimate causal effects in the presence of unmeasured confounding. Traditionally, instrumental variable analyses have been confined to linear models, in which the causal parameter of interest is typically...

Abstract Objectives To develop a methodological proposal to build clinical classifiers using information about signs and symptoms reported by the patient in initial the consultation and laboratory test results. Methods The proposed methodology considers procedures typical of the Bayesian...

Abstract Objectives The Institute of Medicine (IOM 2015. Beyond Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Redefining an Illness. Washington: The National Academies Press) suggested new criteria for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), which requires an...

Abstract Objectives Recent studies show that Test Positivity Rate (TPR) gains a better correlation than incidence with the number of hospitalized patients in COVID-19 pandemic. Nevertheless, epidemiologists remain sceptical concerning the widespread use of this metric for surveillance, and...

Abstract Standard measures of effect, including the risk ratio, the odds ratio, and the risk difference, are associated with a number of well-described shortcomings, and no consensus exists about the conditions under which investigators should choose one effect measure over another. In this...

Abstract The attributable fraction is a common measure in epidemiological research, which quantifies the public health impact of a particular exposure on a particular outcome. Often, the exposure effect may be mediated through a third variable, which lies on the causal pathway between the...

Abstract Confounding by indication is a critical challenge in evaluating the effectiveness of surgical interventions using observational data. The threat from confounding is compounded when using medical claims data due to the inability to measure risk severity. If there are unobserved...

Abstract Regression analyses for time-to-event data are commonly performed by Cox regression. Recently, an alternative method, the pseudo-observation method, has been introduced. This method offers new possibilities of analyzing data exploring cumulative risks on both a multiplicative and an...