Background and aims: Chronic kidney disease (CKD) is a public health challenge worldwide, with adverse consequences of kidney failure, cardiovascular disease (CVD), and premature death. Chronic kidney disease leads to the end stage of renal disease (ESRD), if late/not diagnosed. Competing risk modeling is a major issue in Epidemiology research. In Epidemiology study, sometimes inappropriate met...

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the co...

Among the goals of the molecular epidemiology of infectious disease are to quantify the extent of ongoing transmission of infectious agents and to identify host- and strain-specific risk factors for disease spread. I demonstrate the potential bias in estimates of recent transmission and the impact of risk factors for clustering by using computer simulations to reconstruct populations of tubercu...

The term "selection bias" encompasses various biases in epidemiology. We describe examples of selection bias in case-control studies (eg, inappropriate selection of controls) and cohort studies (eg, informative censoring). We argue that the causal structure underlying the bias in each example is essentially the same: conditioning on a common effect of 2 variables, one of which is either exposur...

Estimates of association from nonrandomized epidemiologic studies are susceptible to two types of error: random error and systematic error. Random error, or sampling error, is often called chance, and decreases toward zero as the sample size increases and the data are more efficiently distributed in the categories of the adjustment variables. The amount of random error in an estimate of associa...

Genetic epidemiology studies often adjust for numerous potential confounders, yet the influences of confounder misclassification and selection bias are rarely considered. We used simulated data to evaluate the effect of confounder misclassification and selection bias in a case-control study of incident myocardial infarction. We show that putative confounders traditionally included in genetic as...

Immortal time is a span of cohort follow-up during which, because of exposure definition, the outcome under study could not occur. Bias from immortal time was first identified in the 1970s in epidemiology in the context of cohort studies of the survival benefit of heart transplantation. It recently resurfaced in pharmacoepidemiology, with several observational studies reporting that various med...

Epidemiology is the study of large numbers of individuals to ascertain incidence, life expectancy, prevalence, time trends, preceding and associated illnesses, and other factors in a disease. Contrasted to laboratory studies in which the experimental conditions can be controlled, epidemiology examines natural events that may have been influenced by health care, economic, and social factors. Epi...

BACKGROUND Infectious disease incidence is often male-biased. Two main hypotheses have been proposed to explain this observation. The physiological hypothesis (PH) emphasizes differences in sex hormones and genetic architecture, while the behavioral hypothesis (BH) stresses gender-related differences in exposure. Surprisingly, the population-level predictions of these hypotheses are yet to be t...