Bayesian graphical modelling: a case‐study in monitoring health outcomes

By David J. Spiegelhalter. 2002

147 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Endocrinology, Diabetes and Metabolism, Statistics and Probability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. A. Sutton
2. N. G. Best
3. David J. Lunn
4. Andrew Thomas
5. N. Cooper
6. K. Abrams
7. M. Mugford
8. David J. Spiegelhalter

In Endocrinology, Diabetes and Metabolism

1. N. G. Best
2. David J. Lunn
3. Andrew Thomas
4. A. Sutton
5. N. Cooper
6. K. Abrams
7. M. Mugford

In Statistics and Probability

1. A. Sutton
2. Georgia Salanti
3. N. G. Best
4. K. Abrams
5. Andrew Thomas
6. David J. Lunn
7. N. Cooper
8. M. Mugford

Citations in the corpus

• A Bayesian model for repeated measures zero-inflated count data with application to outpatient psychiatric service use (2010, background): “As an alternative, one can specify a product normal parameterization for the random effects (Spiegelhalter, 1998; Cooper et al., 2007)”
• The BUGS project: Evolution, critique and future directions (2009, background): “An alternative representation of this model is the directed acyclic graph (DAG; see [27], for example) shown in Figure 1, where each quantity in the model corresponds to a node and links between nodes show direct dependence.”
• Use of Bayesian Markov Chain Monte Carlo Methods to Model Cost-of-Illness Data (2003, methodology): “They provide an accessible description of the nonalgebraic essentials of the model and link computational solutions to inference problems.(14) The graphical models used here are called directed acyclic graphs (DAGs).”
• WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility (2000, methodology): “An alternative representation of this model is the directed acyclic graph (DAG; see, for example, Spiegelhalter 1998 ) shown in Fig. 1, where each quantity in the model corresponds to a node and links between nodes show direct dependence.”
• Bayesian hypothesis testing for psychologists: a tutorial on the Savage-Dickey method. (2010, unknown): “4 shows this model in graphical model notation (for introductions, see Gilks, Thomas, & Spiegelhalter, 1994; Lauritzen, 1996; Lee, 2008; Spiegelhalter, 1998).”