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...tivity analysis methods commonly employed by decision analysts. To set the stage for this example, a brief discussion of decision analysis and sensitivity analysis will be helpful. Decision analysis (=-=Raiffa 1968-=-; Howard 1988; Clemen 1996) can be viewed as one discipline within a spectrum of decision-aiding technologies (Howard 1992). Decision analysis is characterized by its normative orientation, its axioma...

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...mmonly employed by decision analysts. To set the stage for this example, a brief discussion of decision analysis and sensitivity analysis will be helpful. Decision analysis (Raiffa 1968; Howard 1988; =-=Clemen 1996-=-) can be viewed as one discipline within a spectrum of decision-aiding technologies (Howard 1992). Decision analysis is characterized by its normative orientation, its axiomatic foundation, and its us...

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... that Jones’ previous work comprises two separable ideas: the “g to k” transformation and state-based modeling. We relate the concept of state-based modeling to established variable-based RA methods (=-=Klir 1985-=-; Krippendorff 1986), and demonstrate that statebased modeling, when applied to event and decision tree models, is a valuable adjunct to the variable-based sensitivity analyses commonly employed in ri...

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...is methods commonly employed by decision analysts. To set the stage for this example, a brief discussion of decision analysis and sensitivity analysis will be helpful. Decision analysis (Raiffa 1968; =-=Howard 1988-=-; Clemen 1996) can be viewed as one discipline within a spectrum of decision-aiding technologies (Howard 1992). Decision analysis is characterized by its normative orientation, its axiomatic foundatio...

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...’ previous work comprises two separable ideas: the “g to k” transformation and state-based modeling. We relate the concept of state-based modeling to established variable-based RA methods (Klir 1985; =-=Krippendorff 1986-=-), and demonstrate that statebased modeling, when applied to event and decision tree models, is a valuable adjunct to the variable-based sensitivity analyses commonly employed in risk and decision mod...

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...econstructability Modeling For Decision Analysis simultaneously. Specialized graphical display formats have been developed to summarize the results of both one- and two-variable sensitivity analyses (=-=Eschenbach 1992-=-). Analyses involving more than two variables are rarely carried out, however, and threevariable sensitivity analysis is supported in only one of the computational packages available commercially at t...

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...ecision analysis and sensitivity analysis will be helpful. Decision analysis (Raiffa 1968; Howard 1988; Clemen 1996) can be viewed as one discipline within a spectrum of decision-aiding technologies (=-=Howard 1992-=-). Decision analysis is characterized by its normative orientation, its axiomatic foundation, and its use of mathematical models to characterize decision situations. In general, the models developed b...

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...yzing the structure of multivariate categorical data. Jones and his colleagues extended the original variablebased formulation of RA to encompass models defined in terms of system states (Jones 1982; =-=Jones 1985-=-; Jones 1985; Jones 1986; Jones 1989). In this paper, we demonstrate that Jones’ previous work comprises two separable ideas: the “g to k” transformation and state-based modeling. We relate the concep...

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...yzing the structure of multivariate categorical data. Jones and his colleagues extended the original variablebased formulation of RA to encompass models defined in terms of system states (Jones 1982; =-=Jones 1985-=-; Jones 1985; Jones 1986; Jones 1989). In this paper, we demonstrate that Jones’ previous work comprises two separable ideas: the “g to k” transformation and state-based modeling. We relate the concep...

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...categorical data. Jones and his colleagues extended the original variablebased formulation of RA to encompass models defined in terms of system states (Jones 1982; Jones 1985; Jones 1985; Jones 1986; =-=Jones 1989-=-). In this paper, we demonstrate that Jones’ previous work comprises two separable ideas: the “g to k” transformation and state-based modeling. We relate the concept of state-based modeling to establi...

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...ltivariate categorical data. Jones and his colleagues extended the original variable-based formulation of RA to encompass models defined in terms of system states (Jones 1982; Jones 1985; Jones 1985; =-=Jones 1986-=-; Jones 1989). In this paper, we demonstrate that Jones’ previous work comprises two separable ideas: the “g to k” transformation and state-based modeling. We relate the concept of state-based modelin...

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...ing and analyzing the structure of multivariate categorical data. Jones and his colleagues extended the original variablebased formulation of RA to encompass models defined in terms of system states (=-=Jones 1982-=-; Jones 1985; Jones 1985; Jones 1986; Jones 1989). In this paper, we demonstrate that Jones’ previous work comprises two separable ideas: the “g to k” transformation and state-based modeling. We relat...

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...ultivariate categorical data. Jones and his colleagues extended the original variablebased formulation of RA to encompass models defined in terms of system states (Jones 1982; Jones 1985; Jones 1985; =-=Jones 1986-=-; Jones 1989). In this paper, we demonstrate that Jones’ previous work comprises two separable ideas: the “g to k” transformation and state-based modeling. We relate the concept of state-based modelin...

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...s involving more than two variables are rarely carried out, however, and threevariable sensitivity analysis is supported in only one of the computational packages available commercially at this time (=-=Palisade 1997-=-; ADA 1999; TreeAge 1999). Problem formulations involving large numbers of uncertain variables are becoming more common, however, as computer hardware becomes more capable and decision analysis softwa...