Multiattribute utility

Borcherding K, Eppel T, von Winterfeldt D (1991) Comparison of Weighting Judgements in Multiattribute Utility Measurement. Management Science 37 1603-1619... 

To develop the multiattribute utility function, the single-attribute utility functions ( ) and the importance weights (fc ) are determined by assessing preferences between alternatives. Methods of doing so are discussed in Section 3.4. 

Indifference methods are illustrated by the variable probability and certeiinty equivalent methods of eliciting utility functions presented in the previous section. There, indifference points were obtained by varying either probabilities or values of outcomes. Similar approaches have been appUed to develop multiattribute utility or value functions. This approach involves four steps (1) develop the single attribute utility or value functions, (2) assume a functional form for the multiattribute function, (3) assess the indifference point between various multiattribute altematives, and (4) calculate the substitution rate or relative importance of one attribute compared to the other. The single-attribute functions might be developed by indifference methods (i.e., the variable probabihty or certainty equivalent methods) or direct-assessment methods, as discussed later. Indifference points between multiattribute outcomes are obtained through an interactive process in which the values of attributes are systematically increased or decreased. Substitution rates are then obtained from the indifference points. 

Multiactivity charts, 1376-1379 Multi-agent systems (MASs), 174 Multiattribute utility theory (MAUT), 2177, 2183... 

To calculate QALY, we need to estimate the life years of the patient population based on clinical trial data and the health states and their durations during the life years. Health states are usually related to the study endpoints, for example, disease progression or deaths. Multistate analysis can be used to make these estimates. Once the health states are determined, the value or QoL (Q) associated with each state can be established using expert opinion, QoL data collected in the clinical studies, or direct or indirect research. The most frequently used method in practice is direct or indirect research by way of preference survey of health providers and patients. Time trade-off, standard gamble, and rating scale are among the ways to assess the preference of specific health state. As an alternative, indirect research uses questionnaires for health state in several health domains or attributes (e.g., EQ5D) and then to construct a multiattribute utility as a summary measure that reflects preferences both within and across health domains. 

During elicitation of the multiattribute utility function U(H,E,F), the function was considered additive, thus taking into account the existence of preferential independence among the set of payoffs H,E,F. In the human dimension, the relationship between people being exposed to risk and the possible consequences of the events were considered in the environmental dimension, account was taken of the area of vegetation damaged and a monetary loss of 2.000.000 in the financial dimension. 

According to Brito Almeida (2009), the multiattribute utility function is additive, which implies the independence of preferences among the dimensions. Thus the multi-attribute utility function U (h,ej) is obtained based on one-dimensional utility functions U(h), U(e) and U(f), as described below ... 

Due to the independence of the additive multiattribute utility function and independence in the... 

Edwards, W. et al., 1994. SMARTS and SMARTER Improved Simple Methods for Multiattribute Utility Measurement. Organizational Behavior and Human Decision Processes, 60(3) 306-325. 

To estimate the projection (distance) of the manhole cover, the elicitation method, called Equiprobable Intervals, was used. Estimating the risk measures is made from the perspective of Decision Theory. At the same time, a multiattribute utility function U c, c , is elicited from... 

The multiattribute utility functions, by Eq. (4) are combined with the probability density function. Hence, the multidimensional risk measure is calculated. Results of the ranking of the multidimensional risk assessment are shown in Table 2. 

Using the structured elicitation protocol described in Keeney and Raiffa (1976), the multiattribute utility function U(h,v,m) is achieved by choosing from among consequences associated with accidents in pipelines. 

Decision analysis assumes that all relevant considerations in a decision can be assigned to one of the four components initial options, possible consequences, values, and uncertainties. An important tool is the decision tree which reflects the stream of uncertain consequences arising from a decision. A key element of decision analysis is its emphasis on structuring the problem, and decomposing it into a number of more elementary ones. As an example, MAUD is a computer program to structure the decision problem and offer recommendations based on a multiattribute utility analysis. It is a content-free technique applicable to all kinds of decision problems (Humphreys Wishuda 1983). 

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