<p>Directed acyclic graph (DAG) representing conditional independencies (by the absence of arrows) between the genetic instrument <i>Z</i>, the risk factor <i>X</i>, the outcome <i>Y</i> and the confounders <i>U</i>.</p
<p>Instrumental variable models use associations C and A to estimate the causal effect of a risk fac...
The issue of confounding, and the bias it can induce, is a key concern in epidemiology, and yet ther...
Dependency knowledge of the form "x is independent of y once z is known" invariably obeys ...
<p>. Each of the nodes represents a subset of the measured phenotypes . The simplest interpretation...
<p>Directed acyclic graph (DAG) used to guide the analysis and showing hypothesized relationships be...
Directed acyclic graph (DAG) for identifying confounders and minimizing bias prior to the start of t...
<p>Directed acyclic graph of the assumed relationship between education and mortality with paths use...
Directed acyclic graph considered for the selection of confounding variables in the regression model...
<p>Directed acyclic graph showing the framework of Mendelian randomization analyses in this study.</...
<p>Directed acyclic graph, the arrows in blue and red denote the relations that confound the causal ...
Directed acyclic graphs (DAGs) are an intuitive yet rigorous tool to communicate about causal questi...
<p><u>Note</u>: A dashed bi-directed arrow represents the presence of an unmeasured common cause of ...
The goal of most epidemiological studies is to determine an unbiased estimate of the effect of being...
Since confounding obscures the real effect of the exposure, it is important to adequately address co...
Graphical models are useful tools in causal inference, and causal directed acyclic graphs (DAGs) are...
<p>Instrumental variable models use associations C and A to estimate the causal effect of a risk fac...
The issue of confounding, and the bias it can induce, is a key concern in epidemiology, and yet ther...
Dependency knowledge of the form "x is independent of y once z is known" invariably obeys ...
<p>. Each of the nodes represents a subset of the measured phenotypes . The simplest interpretation...
<p>Directed acyclic graph (DAG) used to guide the analysis and showing hypothesized relationships be...
Directed acyclic graph (DAG) for identifying confounders and minimizing bias prior to the start of t...
<p>Directed acyclic graph of the assumed relationship between education and mortality with paths use...
Directed acyclic graph considered for the selection of confounding variables in the regression model...
<p>Directed acyclic graph showing the framework of Mendelian randomization analyses in this study.</...
<p>Directed acyclic graph, the arrows in blue and red denote the relations that confound the causal ...
Directed acyclic graphs (DAGs) are an intuitive yet rigorous tool to communicate about causal questi...
<p><u>Note</u>: A dashed bi-directed arrow represents the presence of an unmeasured common cause of ...
The goal of most epidemiological studies is to determine an unbiased estimate of the effect of being...
Since confounding obscures the real effect of the exposure, it is important to adequately address co...
Graphical models are useful tools in causal inference, and causal directed acyclic graphs (DAGs) are...
<p>Instrumental variable models use associations C and A to estimate the causal effect of a risk fac...
The issue of confounding, and the bias it can induce, is a key concern in epidemiology, and yet ther...
Dependency knowledge of the form "x is independent of y once z is known" invariably obeys ...