Descripción

Fechado: enero 2003

Autores: Statistical Services Centre , Robert Burn

This paper describes a method of quantifying and combining information from causal diagrams to make robust quantitative inferences. It first describes the combining of information from different Scored Causal Diagrams (SCDs) (a tool used in PRA to understand causal-effect relationships of the variables in a system/phenomenon under study), and secondly, how the information can be quantifiable for use in Bayesian Belief Networks (BBNs). It lastly describes how information from different BBNs can be combined to get a pooled BBN. This paper offers a good example of methods for combining qualitative and quantitative information. The paper is associated with outputs from the DFID-funded Natural Resources Systems Programme (Socio-Economic Methodologies Component) project R7033 titled Methodological Framework Integrating Qualitative and Quantitative Approaches for Socio-Economic Survey Work, a collaborative project between the Social and Economic Development Department, Natural Resources Institute and the Statistical Services Centre, The University of Reading.

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