Confounding ≈ ConfoundingConfounding
View article: User's guide to correlation coefficients
User's guide to correlation coefficients Open
When writing a manuscript, we often use words such as perfect, strong, good or weak to name the strength of the relationship between variables. However, it is unclear where a good relationship turns into a strong one. The same strength of …
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Orienting the causal relationship between imprecisely measured traits using GWAS summary data Open
Inference about the causal structure that induces correlations between two traits can be achieved by combining genetic associations with a mediation-based approach, as is done in the causal inference test (CIT). However, we show that measu…
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Mendelian Randomization as an Approach to Assess Causality Using Observational Data Open
Mendelian randomization refers to an analytic approach to assess the causality of an observed association between a modifiable exposure or risk factor and a clinically relevant outcome. It presents a valuable tool, especially when randomiz…
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Robust causal inference using directed acyclic graphs: the R package ‘dagitty’ Open
Directed acyclic graphs (DAGs), which offer systematic representations of causal relationships, have become an established framework for the analysis of causal inference in epidemiology, often being used to determine covariate adjustment s…
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Prevalence, incidence and mortality from cardiovascular disease in patients with pooled and specific severe mental illness: a large‐scale meta‐analysis of 3,211,768 patients and 113,383,368 controls Open
People with severe mental illness (SMI) – schizophrenia, bipolar disorder and major depressive disorder – appear at risk for cardiovascular disease (CVD), but a comprehensive meta‐analysis is lacking. We conducted a large‐scale meta‐analys…
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Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies Open
False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association…
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Epidemiology: An introduction Open
1. Introduction to Epidemiologic Thinking 2. Pioneers in Epidemiology and Public Health 3. What is Causation? 4. Measuring Disease Occurrence and Causal Effects 5. Types of Epidemiologic Studies 6. Infectious Disease Epidemiology 7. Dealin…
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A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures Open
Unlike inferential approaches that examine the effects of individual exposures while holding other exposures constant, methods like quantile g-computation that can estimate the effect of a mixture are essential for understanding the effect…
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Protection of BNT162b2 Vaccine Booster against Covid-19 in Israel Open
In this study involving participants who were 60 years of age or older and had received two doses of the BNT162b2 vaccine at least 5 months earlier, we found that the rates of confirmed Covid-19 and severe illness were substantially lower …
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Taiwan’s National Health Insurance Research Database: past and future Open
Taiwan's National Health Insurance Research Database (NHIRD) exemplifies a population-level data source for generating real-world evidence to support clinical decisions and health care policy-making. Like with all claims databases, there h…
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Mendelian randomisation for mediation analysis: current methods and challenges for implementation Open
Mediation analysis seeks to explain the pathway(s) through which an exposure affects an outcome. Traditional, non-instrumental variable methods for mediation analysis experience a number of methodological difficulties, including bias due t…
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An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings Open
Background Mendelian randomization (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilizing genetic variants that are instru…
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The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects* Open
We show that the neighborhoods in which children grow up shape their earnings, college attendance rates, and fertility and marriage patterns by studying more than 7 million families who move across commuting zones and counties in the Unite…
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Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study Open
Objectives United States government scientists estimate that COVID-19 may kill tens of thousands of Americans. Many of the pre-existing conditions that increase the risk of death in those with COVID-19 are the same diseases that are affect…
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Triglyceride-Rich Lipoproteins and Atherosclerotic Cardiovascular Disease Open
Scientific interest in triglyceride-rich lipoproteins has fluctuated over the past many years, ranging from beliefs that these lipoproteins cause atherosclerotic cardiovascular disease (ASCVD) to being innocent bystanders. Correspondingly,…
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BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants Open
Overweight and obesity is associated with increased risk of all cause mortality and the nadir of the curve was observed at BMI 23-24 among never smokers, 22-23 among healthy never smokers, and 20-22 with longer durations of follow-up. The …
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Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations Open
Background Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal effects. This review examined the use of DAGs in applied health research …
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Making Sense of Sensitivity: Extending Omitted Variable Bias Open
Summary We extend the omitted variable bias framework with a suite of tools for sensitivity analysis in regression models that does not require assumptions on the functional form of the treatment assignment mechanism nor on the distributio…
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Age as a Confounding Factor for the Accurate Non-Invasive Diagnosis of Advanced NAFLD Fibrosis Open
The NFS and FIB-4 scores have similar accuracy for advanced fibrosis in patients aged >35 years. However, the specificity for advanced fibrosis is unacceptably low in patients aged ≥65 years, resulting in a high false positive rate. New th…
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Sparse data bias: a problem hiding in plain sight Open
Effects of treatment or other exposure on outcome events are commonly measured by ratios of risks, rates, or odds. Adjusted versions of these measures are usually estimated by maximum likelihood regression (eg, logistic, Poisson, or Cox mo…
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Blood pressure variability and cardiovascular disease: systematic review and meta-analysis Open
PROSPERO CRD42014015695.
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Multivariable Mendelian Randomization and Mediation Open
Mendelian randomization (MR) is the use of genetic variants associated with an exposure to estimate the causal effect of that exposure on an outcome. Mediation analysis is the method of decomposing the effects of an exposure on an outcome,…
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Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score Open
Mendelian randomization (MR) is a method of exploiting genetic variation to unbiasedly estimate a causal effect in presence of unmeasured confounding. MR is being widely used in epidemiology and other related areas of population science. I…
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Analysis of matched case-control studies Open
There are two common misconceptions about case-control studies: that matching in itself eliminates (controls) confounding by the matching factors, and that if matching has been performed, then a “matched analysis” is required. However, mat…
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Environmental risk factors for autism: an evidence-based review of systematic reviews and meta-analyses Open
Compared to genetic studies of ASD, studies of environmental risk factors are in their infancy and have significant methodological limitations. Future studies of ASD risk factors would benefit from a developmental psychopathology approach,…
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An introduction to inverse probability of treatment weighting in observational research Open
In this article we introduce the concept of inverse probability of treatment weighting (IPTW) and describe how this method can be applied to adjust for measured confounding in observational research, illustrated by a clinical example from …
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Update of the MDS research criteria for prodromal Parkinson's disease Open
The MDS Research Criteria for Prodromal PD allow the diagnosis of prodromal Parkinson's disease using an evidence‐based conceptual framework, which was designed to be updated as new evidence becomes available. New prospective evidence of p…
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Control of Confounding and Reporting of Results in Causal Inference Studies. Guidance for Authors from Editors of Respiratory, Sleep, and Critical Care Journals Open
International audience
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Effects of temperature and humidity on the daily new cases and new deaths of COVID-19 in 166 countries Open
The coronavirus disease 2019 (COVID-19) pandemic is the defining global health crisis of our time and the greatest challenge facing the world. Meteorological parameters are reportedly crucial factors affecting respiratory infectious diseas…
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Statistical primer: propensity score matching and its alternatives† Open
Propensity score (PS) methods offer certain advantages over more traditional regression methods to control for confounding by indication in observational studies. Although multivariable regression models adjust for confounders by modelling…