Research on probabilistic information processing

NASA Technical Reports Server (NTRS)

Edwards, W.

1973-01-01

The work accomplished on probabilistic information processing (PIP) is reported. The research proposals and decision analysis are discussed along with the results of research on MSC setting, multiattribute utilities, and Bayesian research. Abstracts of reports concerning the PIP research are included.

Spaceborne power systems preference analyses. Volume 1: Summary

NASA Technical Reports Server (NTRS)

Smith, J. H.; Feinberg, A.; Miles, R. F., Jr.

1985-01-01

Sixteen alternative spaceborne nuclear power system concepts were ranked using multiattribute decision analysis to identify promising concepts for further technology development. Four groups interviewed were: safety, systems definition and design, technology assessment, and mission analysis. The ranking results were consistent from group and for different utility function models for individuals.

Application fuzzy multi-attribute decision analysis method to prioritize project success criteria

NASA Astrophysics Data System (ADS)

Phong, Nguyen Thanh; Quyen, Nguyen Le Hoang Thuy To

2017-11-01

Project success is a foundation for project owner to manage and control not only for the current project but also for future potential projects in construction companies. However, identifying the key success criteria for evaluating a particular project in real practice is a challenging task. Normally, it depends on a lot of factors, such as the expectation of the project owner and stakeholders, triple constraints of the project (cost, time, quality), and company's mission, vision, and objectives. Traditional decision-making methods for measuring the project success are usually based on subjective opinions of panel experts, resulting in irrational and inappropriate decisions. Therefore, this paper introduces a multi-attribute decision analysis method (MADAM) for weighting project success criteria by using fuzzy Analytical Hierarchy Process approach. It is found that this method is useful when dealing with imprecise and uncertain human judgments in evaluating project success criteria. Moreover, this research also suggests that although cost, time, and quality are three project success criteria projects, the satisfaction of project owner and acceptance of project stakeholders with the completed project criteria is the most important criteria for project success evaluation in Vietnam.

Using Multiattribute Utility Theory as a Priority-Setting Tool in Human Services Planning.

ERIC Educational Resources Information Center

Camasso, Michael J.; Dick, Janet

1993-01-01

The feasibility of applying multiattribute utility theory to the needs assessment and priority-setting activities of human services planning councils was studied in Essex County (New Jersey). Decision-making and information filtering processes are explored in the context of community planning. (SLD)

Screening and Evaluation Tool (SET) Users Guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pincock, Layne

This document is the users guide to using the Screening and Evaluation Tool (SET). SET is a tool for comparing multiple fuel cycle options against a common set of criteria and metrics. It does this using standard multi-attribute utility decision analysis methods.

Propulsion Airframe Aeroacoustics Technology Evaluation and Selection Using a Multi-Attribute Decision Making Process and Non-Deterministic Design

NASA Technical Reports Server (NTRS)

Burg, Cecile M.; Hill, Geoffrey A.; Brown, Sherilyn A.; Geiselhart, Karl A.

2004-01-01

The Systems Analysis Branch at NASA Langley Research Center has investigated revolutionary Propulsion Airframe Aeroacoustics (PAA) technologies and configurations for a Blended-Wing-Body (BWB) type aircraft as part of its research for NASA s Quiet Aircraft Technology (QAT) Project. Within the context of the long-term NASA goal of reducing the perceived aircraft noise level by a factor of 4 relative to 1997 state of the art, major configuration changes in the propulsion airframe integration system were explored with noise as a primary design consideration. An initial down-select and assessment of candidate PAA technologies for the BWB was performed using a Multi-Attribute Decision Making (MADM) process consisting of organized brainstorming and decision-making tools. The assessments focused on what effect the PAA technologies had on both the overall noise level of the BWB and what effect they had on other major design considerations such as weight, performance and cost. A probabilistic systems analysis of the PAA configurations that presented the best noise reductions with the least negative impact on the system was then performed. Detailed results from the MADM study and the probabilistic systems analysis will be published in the near future.

A Market-oriented Approach To Maximizing Product Benefits: Cases in U.S. Forest Products Industries

Treesearch

Vijay S. Reddy; Robert J. Bush; Ronen Roudik

1996-01-01

Conjoint analysis, a decompositional customer preference modelling technique, has seen little application to forest products. However, the technique provides useful information for marketing decisions by quantifying consumer preference functions for multiattribute product alternatives. The results of a conjoint analysis include the contribution of each attribute and...

Multi-Attribute Consensus Building Tool

ERIC Educational Resources Information Center

Shyyan, Vitaliy; Christensen, Laurene; Thurlow, Martha; Lazarus, Sheryl

2013-01-01

The Multi-Attribute Consensus Building (MACB) method is a quantitative approach for determining a group's opinion about the importance of each item (strategy, decision, recommendation, policy, priority, etc.) on a list (Vanderwood, & Erickson, 1994). This process enables a small or large group of participants to generate and discuss a set…

Evaluate the use of tanning agent in leather industry using material flow analysis, life cycle assessment and fuzzy multi-attribute decision making (FMADM)

NASA Astrophysics Data System (ADS)

Alfarisi, Salman; Sutono, Sugoro Bhakti; Sutopo, Wahyudi

2017-11-01

Tanning industry is one of the companies that produce many pollutants and cause the negative impact on the environment. In the production process of tanning leather, the use of input material need to be evaluated. The problem of waste, not only have a negative impact on the environment, but also human health. In this study, the impact of mimosa as vegetable tanning agent evaluated. This study will provide alternative solutions for improvements to the use of vegetable tanning agent. The alternative solution is change mimosa with indusol, gambier, and dulcotan. This study evaluate the vegetable tanning of some aspects using material flow analysis and life cycle assessment approach. Life cycle assessment (LCA) is used to evaluate the environmental impact of vegetable tanning agent. Alternative solution selection using fuzzy multi-attribute decision making (FMADM) approach. Results obtained by considering the environment, human toxicity, climate change, and marine aquatic ecotoxicity, is to use dulcotan.

Experimental analysis of multi-attribute decision-making based on Atanassov intuitionistic fuzzy sets: a discussion of anchor dependency and accuracy functions

NASA Astrophysics Data System (ADS)

Chen, Ting-Yu

2012-06-01

This article presents a useful method for relating anchor dependency and accuracy functions to multiple attribute decision-making (MADM) problems in the context of Atanassov intuitionistic fuzzy sets (A-IFSs). Considering anchored judgement with displaced ideals and solution precision with minimal hesitation, several auxiliary optimisation models have proposed to obtain the optimal weights of the attributes and to acquire the corresponding TOPSIS (the technique for order preference by similarity to the ideal solution) index for alternative rankings. Aside from the TOPSIS index, as a decision-maker's personal characteristics and own perception of self may also influence the direction in the axiom of choice, the evaluation of alternatives is conducted based on distances of each alternative from the positive and negative ideal alternatives, respectively. This article originates from Li's [Li, D.-F. (2005), 'Multiattribute Decision Making Models and Methods Using Intuitionistic Fuzzy Sets', Journal of Computer and System Sciences, 70, 73-85] work, which is a seminal study of intuitionistic fuzzy decision analysis using deduced auxiliary programming models, and deems it a benchmark method for comparative studies on anchor dependency and accuracy functions. The feasibility and effectiveness of the proposed methods are illustrated by a numerical example. Finally, a comparative analysis is illustrated with computational experiments on averaging accuracy functions, TOPSIS indices, separation measures from positive and negative ideal alternatives, consistency rates of ranking orders, contradiction rates of the top alternative and average Spearman correlation coefficients.

Tools, information sources, and methods used in deciding on drug availability in HMOs.

PubMed

Barner, J C; Thomas, J

1998-01-01

The use and importance of specific decision-making tools, information sources, and drug-use management methods in determining drug availability and use in HMOs were studied. A questionnaire was sent to 303 randomly selected HMOs. Respondents were asked to rate their use of each of four formal decision-making tools and its relative importance, as well as the use and importance of eight information sources and 11 methods for managing drug availability and use, on a 5-point scale. The survey response rate was 28%. Approximately half of the respondents reported that their HMOs used decision analysis or multiattribute analysis in deciding on drug availability. If used, these tools were rated as very important. There were significant differences in levels of use by HMO type, membership size, and age. Journal articles and reference books were reported most often as information sources. Retrospective drug-use review was used very often and perceived to be very important in managing drug use. Other management methods were used only occasionally, but the importance placed on these tools when used ranged from moderately to very important. Older organizations used most of the management methods more often than did other HMOs. Decision analysis and multiattribute analysis were the most commonly used tools for deciding on which drugs to make available to HMO members, and reference books and journal articles were the most commonly used information sources. Retrospective and prospective drug-use reviews were the most commonly applied methods for managing HMO members' access to drugs.

Selecting essential information for biosurveillance--a multi-criteria decision analysis.

PubMed

Generous, Nicholas; Margevicius, Kristen J; Taylor-McCabe, Kirsten J; Brown, Mac; Daniel, W Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.

Integrating Cost as an Independent Variable Analysis with Evolutionary Acquisition - A Multiattribute Design Evaluation Approach

DTIC Science & Technology

2003-03-01

within the Automated Cost Estimating Integrated Tools ( ACEIT ) software suite (version 5.x). With this capability, one can set cost targets or time...not allow the user to vary more than one decision variable. This limitation of the ACEIT approach thus hinders a holistic view when attempting to

Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies

NASA Astrophysics Data System (ADS)

Liu, Qian; Li, Huajiao; Liu, Xueyong; Jiang, Meihui

2018-04-01

In the stock market, there are widespread information connections between economic agents. Listed companies can obtain mutual information about investment decisions from common shareholders, and the extent of sharing information often determines the relationships between listed companies. Because different shareholder compositions and investment shares lead to different formations of the company's governance mechanisms, we map the investment relationships between shareholders to the multi-attribute dimensional spaces of the listed companies (each shareholder investment in a company is a company dimension). Then, we construct the listed company's information network based on co-shareholder relationships. The weights for the edges in the information network are measured with the Euclidean distance between the listed companies in the multi-attribute dimension space. We define two indices to analyze the information network's features. We conduct an empirical study that analyzes Chinese listed companies' information networks. The results from the analysis show that with the diversification and decentralization of shareholder investments, almost all Chinese listed companies exchanged information through common shareholder relationships, and there is a gradual reduction in information sharing capacity between listed companies that have common shareholders. This network analysis has benefits for risk management and portfolio investments.

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Fuzzy sets, rough sets, and modeling evidence: Theory and Application. A Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection

NASA Technical Reports Server (NTRS)

Dekorvin, Andre

1992-01-01

The Dempster-Shafer theory of evidence is applied to a multiattribute decision making problem whereby the decision maker (DM) must compromise with available alternatives, none of which exactly satisfies his ideal. The decision mechanism is constrained by the uncertainty inherent in the determination of the relative importance of each attribute element and the classification of existing alternatives. The classification of alternatives is addressed through expert evaluation of the degree to which each element is contained in each available alternative. The relative importance of each attribute element is determined through pairwise comparisons of the elements by the decision maker and implementation of a ratio scale quantification method. Then the 'belief' and 'plausibility' that an alternative will satisfy the decision maker's ideal are calculated and combined to rank order the available alternatives. Application to the problem of selecting computer software is given.

A new multicriteria risk mapping approach based on a multiattribute frontier concept.

PubMed

Yemshanov, Denys; Koch, Frank H; Ben-Haim, Yakov; Downing, Marla; Sapio, Frank; Siltanen, Marty

2013-09-01

Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that typically require prior knowledge of the risk components' importance. Such information is often nonexistent for many invasive pests. This study proposes a new approach for building integrated risk maps using the principle of a multiattribute efficient frontier and analyzing the partial order of elements of a risk map as distributed in multidimensional criteria space. The integrated risks are estimated as subsequent multiattribute frontiers in dimensions of individual risk criteria. We demonstrate the approach with the example of Agrilus biguttatus Fabricius, a high-risk pest that may threaten North American oak forests in the near future. Drawing on U.S. and Canadian data, we compare the performance of the multiattribute ranking against a multicriteria linear weighted averaging technique in the presence of uncertainties, using the concept of robustness from info-gap decision theory. The results show major geographic hotspots where the consideration of tradeoffs between multiple risk components changes integrated risk rankings. Both methods delineate similar geographical regions of high and low risks. Overall, aggregation based on a delineation of multiattribute efficient frontiers can be a useful tool to prioritize risks for anticipated invasive pests, which usually have an extremely poor prior knowledge base. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Multiattribute evaluation in formulary decision making as applied to calcium-channel blockers.

PubMed

Schumacher, G E

1991-02-01

The use of multiattribute utility theory (MAUT) to make a formulary decision involving calcium-channel blockers (CCBs) is described. The MAUT method is a procedure for identifying, characterizing, and comparing the many variables that may affect a decision. Although applications in pharmacy have been infrequent, MAUT should be particularly appealing to formulary committees. The steps of the MAUT method are (1) determine the viewpoint of the decision makers, (2) identify the decision alternatives, (3) identify the attributes to be evaluated, (4) identify the factors to be used in evaluating the attributes, (5) establish a utility scale for scoring each factor, (6) transform the values for each factor to its utility scale, (7) determine weights for each attribute and factor, (8) calculate the total utility score for each decision alternative, (9) determine which decision alternative has the greatest total score, and (10) perform a sensitivity analysis. The viewpoint of a formulary committee in a health maintenance organization was simulated to develop a model for using the MAUT method to compare CCBs for single-agent therapy of chronic stable angina in ambulatory patients for one year. The attributes chosen were effectiveness, safety, patient acceptance, and cost and weighted 36%, 29%, 21%, and 14%, respectively, as contributions to the evaluation. The rank order of the decision alternatives was (1) generic verapamil, (2) brand-name verapamil, (3) diltiazem, (4) nicardipine, and (5) nifedipine. The MAUT method provides a standardized yet flexible format for comparing and selecting among formulary alternatives.

Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis

PubMed Central

Generous, Nicholas; Margevicius, Kristen J.; Taylor-McCabe, Kirsten J.; Brown, Mac; Daniel, W. Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system. PMID:24489748

Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

PubMed

Li, Yan

2017-05-25

The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

Use of multiattribute utility theory for formulary management in a health system.

PubMed

Chung, Seonyoung; Kim, Sooyon; Kim, Jeongmee; Sohn, Kieho

2010-01-15

The application, utility, and flexibility of the multiattribute utility theory (MAUT) when used as a formulary decision methodology in a Korean medical center were evaluated. A drug analysis model using MAUT consisting of 10 steps was designed for two drug classes of dihydropyridine calcium channel blockers (CCBs) and angiotensin II receptor blockers (ARBs). These two drug classes contain the most diverse agents among cardiovascular drugs on Samsung Medical Center's drug formulary. The attributes identified for inclusion in the drug analysis model were effectiveness, safety, patient convenience, and cost, with relative weights of 50%, 30%, 10%, and 10%, respectively. The factors were incorporated into the model to quantify the contribution of each attribute. For each factor, a utility scale of 0-100 was established, and the total utility score for each alternative was calculated. An attempt was made to make the model adaptable to changing health care and regulatory circumstances. The analysis revealed amlodipine besylate to be an alternative agent, with the highest total utility score among the dihydropyridine CCBs, while barnidipine hydrochloride had the lowest score. For ARBs, losartan potassium had the greatest total utility score, while olmesartan medoxomil had the lowest. A drug analysis model based on the MAUT was successfully developed and used in making formulary decisions for dihydropyridine CCBs and ARBs for a Korean health system. The model incorporates sufficient utility and flexibility of a drug's attributes and can be used as an alternative decision-making tool for formulary management in health systems.

Multiattribute Decision Modeling Techniques: A Comparative Analysis

DTIC Science & Technology

1988-08-01

Analytic Hierarchy Process ( AHP ). It is structurally similar to SMART, but elicitation methods are different and there are several algorithms for...reconciliation of inconsistent judgments and for consistency checks that are not available in any of the utility procedures. The AHP has been applied...of commercially available software packages that implement the AHP algorithms. Elicitation Methods. The AHP builds heavily on value trees, which

Toolbox or Adjustable Spanner? A Critical Comparison of Two Metaphors for Adaptive Decision Making

ERIC Educational Resources Information Center

Söllner, Anke; Bröder, Arndt

2016-01-01

For multiattribute decision tasks, different metaphors exist that describe the process of decision making and its adaptation to diverse problems and situations. Multiple strategy models (MSMs) assume that decision makers choose adaptively from a set of different strategies (toolbox metaphor), whereas evidence accumulation models (EAMs) hold that a…

Public Affairs Decision Making in the U.S. Air Force: An Application of Multiattribute Utility Theory.

ERIC Educational Resources Information Center

David, Prabu; Pierson, Michael M.

1998-01-01

Contributes to scholarship on public relations decision making and public relations theory. Examines decision making by United States Air Force public affairs personnel. Finds that only 48% of the decisions fit the public relations excellence criteria of accommodation and long-term relationship building. Finds also a negative correlation between…

Multi-Attribute Tradespace Exploration in Space System Design

NASA Astrophysics Data System (ADS)

Ross, A. M.; Hastings, D. E.

2002-01-01

The complexity inherent in space systems necessarily requires intense expenditures of resources both human and monetary. The high level of ambiguity present in the early design phases of these systems causes long, highly iterative, and costly design cycles. This paper looks at incorporating decision theory methods into the early design processes to streamline communication of wants and needs among stakeholders and between levels of design. Communication channeled through formal utility interviews and analysis enables engineers to better understand the key drivers for the system and allows a more thorough exploration of the design tradespace. Multi-Attribute Tradespace Exploration (MATE), an evolving process incorporating decision theory into model and simulation- based design, has been applied to several space system case studies at MIT. Preliminary results indicate that this process can improve the quality of communication to more quickly resolve project ambiguity, and enable the engineer to discover better value designs for multiple stakeholders. MATE is also being integrated into a concurrent design environment to facilitate the transfer knowledge of important drivers into higher fidelity design phases. Formal utility theory provides a mechanism to bridge the language barrier between experts of different backgrounds and differing needs (e.g. scientists, engineers, managers, etc). MATE with concurrent design couples decision makers more closely to the design, and most importantly, maintains their presence between formal reviews.

Robust Sensitivity Analysis for Multi-Attribute Deterministic Hierarchical Value Models

DTIC Science & Technology

2002-03-01

such as weighted sum method, weighted 5 product method, and the Analytic Hierarchy Process ( AHP ). This research focuses on only weighted sum...different groups. They can be termed as deterministic, stochastic, or fuzzy multi-objective decision methods if they are classified according to the...weighted product model (WPM), and analytic hierarchy process ( AHP ). His method attempts to identify the most important criteria weight and the most

Coding Theory Information Theory and Radar

DTIC Science & Technology

2005-01-01

the design and synthesis of artificial multiagent systems and for the understanding of human decision-making processes. This... altruism that may exist in a complex society. SGT derives its ability to account simultaneously for both group and individual interests from the structure of ...satisficing decision theory as a model of human decision mak- ing. 2 Multi-Attribute Decision Making Many decision problems involve the consideration of

Application of the fuzzy topsis multi-attribute decision making method to determine scholarship recipients

NASA Astrophysics Data System (ADS)

Irvanizam, I.

2018-03-01

Some scholarships have been routinely offered by Ministry of Research, Technology and Higher Education of the Republic of Indonesia for students at Syiah Kuala University. In reality, the scholarship selection process is becoming subjective and highly complex problem. Multi-Attribute Decision Making (MADM) techniques can be a solution in order to solve scholarship selection problem. In this study, we demonstrated the application of a fuzzy TOPSIS as an MADM technique by using a numerical example in order to calculate a triangular fuzzy number for the fuzzy data onto a normalized weight. We then use this normalized value to construct the normalized fuzzy decision matrix. We finally use the fuzzy TOPSIS to rank alternatives in descending order based on the relative closeness to the ideal solution. The result in terms of final ranking shows slightly different from the previous work.

Texas Urban Triangle : pilot study to implement a spatial decision support system (SDSS) for sustainable mobility.

DOT National Transportation Integrated Search

2011-03-01

This project addressed sustainable transportation in the Texas Urban Triangle (TUT) by conducting a pilot : project at the county scale. The project tested and developed the multi-attribute Spatial Decision Support : System (SDSS) developed in 2009 u...

Technology selection for ballast water treatment by multi-stakeholders: A multi-attribute decision analysis approach based on the combined weights and extension theory.

PubMed

Ren, Jingzheng

2018-01-01

This objective of this study is to develop a generic multi-attribute decision analysis framework for ranking the technologies for ballast water treatment and determine their grades. An evaluation criteria system consisting of eight criteria in four categories was used to evaluate the technologies for ballast water treatment. The Best-Worst method, which is a subjective weighting method and Criteria importance through inter-criteria correlation method, which is an objective weighting method, were combined to determine the weights of the evaluation criteria. The extension theory was employed to prioritize the technologies for ballast water treatment and determine their grades. An illustrative case including four technologies for ballast water treatment, i.e. Alfa Laval (T 1 ), Hyde (T 2 ), Unitor (T 3 ), and NaOH (T 4 ), were studied by the proposed method, and the Hyde (T 2 ) was recognized as the best technology. Sensitivity analysis was also carried to investigate the effects of the combined coefficients and the weights of the evaluation criteria on the final priority order of the four technologies for ballast water treatment. The sum weighted method and the TOPSIS was also employed to rank the four technologies, and the results determined by these two methods are consistent to that determined by the proposed method in this study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of infectious diseases and clinical microbiology specialists' preferences for hand hygiene: analysis using the multi-attribute utility theory and the analytic hierarchy process methods.

PubMed

Suner, Aslı; Oruc, Ozlem Ege; Buke, Cagri; Ozkaya, Hacer Deniz; Kitapcioglu, Gul

2017-08-31

Hand hygiene is one of the most effective attempts to control nosocomial infections, and it is an important measure to avoid the transmission of pathogens. However, the compliance of healthcare workers (HCWs) with hand washing is still poor worldwide. Herein, we aimed to determine the best hand hygiene preference of the infectious diseases and clinical microbiology (IDCM) specialists to prevent transmission of microorganisms from one patient to another. Expert opinions regarding the criteria that influence the best hand hygiene preference were collected through a questionnaire via face-to-face interviews. Afterwards, these opinions were examined with two widely used multi-criteria decision analysis (MCDA) methods, the Multi-Attribute Utility Theory (MAUT) and the Analytic Hierarchy Process (AHP). A total of 15 IDCM specialist opinions were collected from diverse private and public hospitals located in İzmir, Turkey. The mean age of the participants was 49.73 ± 8.46, and the mean experience year of the participants in their fields was 17.67 ± 11.98. The findings that we obtained through two distinct decision making methods, the MAUT and the AHP, suggest that alcohol-based antiseptic solution (ABAS) has the highest utility (0.86) and priority (0.69) among the experts' choices. In conclusion, the MAUT and the AHP, decision models developed here indicate that rubbing the hands with ABAS is the most favorable choice for IDCM specialists to prevent nosocomial infection.

Impact of Decision Criteria on Federal Aviation Administration Certification of Military Commercial Derivative Aircraft

DTIC Science & Technology

2012-03-01

Capt Low was a member of the Sigma Iota Epsilon professional management fraternity. He has performed as an on-equipment and off-equipment...FAA Certification, Military Commercial Derivative Aircraft, Multi-Attribute Decision Making 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

A decision aid for intensity-modulated radiation-therapy plan selection in prostate cancer based on a prognostic Bayesian network and a Markov model.

PubMed

Smith, Wade P; Doctor, Jason; Meyer, Jürgen; Kalet, Ira J; Phillips, Mark H

2009-06-01

The prognosis of cancer patients treated with intensity-modulated radiation-therapy (IMRT) is inherently uncertain, depends on many decision variables, and requires that a physician balance competing objectives: maximum tumor control with minimal treatment complications. In order to better deal with the complex and multiple objective nature of the problem we have combined a prognostic probabilistic model with multi-attribute decision theory which incorporates patient preferences for outcomes. The response to IMRT for prostate cancer was modeled. A Bayesian network was used for prognosis for each treatment plan. Prognoses included predicting local tumor control, regional spread, distant metastases, and normal tissue complications resulting from treatment. A Markov model was constructed and used to calculate a quality-adjusted life-expectancy which aids in the multi-attribute decision process. Our method makes explicit the tradeoffs patients face between quality and quantity of life. This approach has advantages over current approaches because with our approach risks of health outcomes and patient preferences determine treatment decisions.

Decision theory and the evaluation of risks and benefits of clinical trials.

PubMed

Bernabe, Rosemarie D C; van Thiel, Ghislaine J M W; Raaijmakers, Jan A M; van Delden, Johannes J M

2012-12-01

Research ethics committees (RECs) are tasked to assess the risks and the benefits of a clinical trial. In previous studies, it was shown that RECs find this task difficult, if not impossible, to do. The current approaches to benefit-risk assessment (i.e. Component Analysis and the Net Risk Test) confound the various risk-benefit tasks, and as such, make balancing impossible. In this article, we show that decision theory, specifically through the expected utility theory and multiattribute utility theory, enable for an explicit and ethically weighted risk-benefit evaluation. This makes a balanced ethical justification possible, and thus a more rationally defensible decision making. Copyright © 2012 Elsevier Ltd. All rights reserved.

Strategic Technology Investment Analysis: An Integrated System Approach

NASA Technical Reports Server (NTRS)

Adumitroaie, V.; Weisbin, C. R.

2010-01-01

Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce. This paper describes an approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis. The evaluation of the degree of robustness of the recommended portfolio provides the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy nontechnical constraints. The methodology is presented in the context of assessing capability development portfolios for NASA technology programs.

Decision Making for Pap Testing among Pacific Islander Women

ERIC Educational Resources Information Center

Weiss, Jie W.; Mouttapa, Michele; Sablan-Santos, Lola; DeGuzman Lacsamana, Jasmine; Quitugua, Lourdes; Park Tanjasiri, Sora

2016-01-01

This study employed a Multi-Attribute Utility (MAU) model to examine the Pap test decision-making process among Pacific Islanders (PI) residing in Southern California. A total of 585 PI women were recruited through social networks from Samoan and Tongan churches, and Chamorro family clans. A questionnaire assessed Pap test knowledge, beliefs and…

Relative Saliency in Change Signals Affects Perceptual Comparison and Decision Processes in Change Detection

ERIC Educational Resources Information Center

Yang, Cheng-Ta

2011-01-01

Change detection requires perceptual comparison and decision processes on different features of multiattribute objects. How relative salience between two feature-changes influences the processes has not been addressed. This study used the systems factorial technology to investigate the processes when detecting changes in a Gabor patch with visual…

Some induced intuitionistic fuzzy aggregation operators applied to multi-attribute group decision making

NASA Astrophysics Data System (ADS)

Su, Zhi-xin; Xia, Guo-ping; Chen, Ming-yuan

2011-11-01

In this paper, we define various induced intuitionistic fuzzy aggregation operators, including induced intuitionistic fuzzy ordered weighted averaging (OWA) operator, induced intuitionistic fuzzy hybrid averaging (I-IFHA) operator, induced interval-valued intuitionistic fuzzy OWA operator, and induced interval-valued intuitionistic fuzzy hybrid averaging (I-IIFHA) operator. We also establish various properties of these operators. And then, an approach based on I-IFHA operator and intuitionistic fuzzy weighted averaging (WA) operator is developed to solve multi-attribute group decision-making (MAGDM) problems. In such problems, attribute weights and the decision makers' (DMs') weights are real numbers and attribute values provided by the DMs are intuitionistic fuzzy numbers (IFNs), and an approach based on I-IIFHA operator and interval-valued intuitionistic fuzzy WA operator is developed to solve MAGDM problems where the attribute values provided by the DMs are interval-valued IFNs. Furthermore, induced intuitionistic fuzzy hybrid geometric operator and induced interval-valued intuitionistic fuzzy hybrid geometric operator are proposed. Finally, a numerical example is presented to illustrate the developed approaches.

Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting.

PubMed

Carpenter, Stephanie M; Yates, J Frank; Preston, Stephanie D; Chen, Lydia

2016-01-01

Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional "coherence shifting," the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed.

Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting

PubMed Central

Carpenter, Stephanie M.; Yates, J. Frank; Preston, Stephanie D.; Chen, Lydia

2016-01-01

Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional “coherence shifting,” the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed. PMID:26986752

Perceptual grouping does not affect multi-attribute decision making if no processing costs are involved.

PubMed

Ettlin, Florence; Bröder, Arndt

2015-05-01

Adaptive strategy selection implies that a decision strategy is chosen based on its fit to the task and situation. However, other aspects, such as the way information is presented, can determine information search behavior; especially when the application of certain strategies over others is facilitated. But are such display effects on multi-attribute decisions also at work when the manipulation does not entail differential costs for different decision strategies? Three Mouselab experiments with hidden information and one eye tracking experiment with an open information board revealed that decision behavior is unaffected by purely perceptual manipulations of the display based on Gestalt principles; that is, based on manipulations that induce no noteworthy processing costs for different information search patterns. We discuss our results in the context of previous findings on display effects; specifically, how the combination of these findings and our results reveal the crucial role of differential processing costs for different strategies for the emergence of display effects. This finding describes a boundary condition of the commonly acknowledged influence of information displays and is in line with the ideas of adaptive strategy selection and cost-benefit tradeoffs. Copyright © 2015. Published by Elsevier B.V.

Schizophrenia: multi-attribute utility theory approach to selection of atypical antipsychotics.

PubMed

Bettinger, Tawny L; Shuler, Garyn; Jones, Donnamaria R; Wilson, James P

2007-02-01

Current guidelines/algorithms recommend atypical antipsychotics as first-line agents for the treatment of schizophrenia. Because there are extensive healthcare costs associated with the treatment of schizophrenia, many institutions and health systems are faced with making restrictive formulary decisions regarding the use of atypical antipsychotics. Often, medication acquisition costs are the driving force behind formulary decisions, while other treatment factors are not considered. To apply a multi-attribute utility theory (MAUT) analysis to aid in the selection of a preferred agent among the atypical antipsychotics for the treatment of schizophrenia. Five atypical antipsychotics (risperidone, olanzapine, quetiapine, ziprasidone, aripiprazole) were selected as the alternative agents to be included in the MAUT analysis. The attributes identified for inclusion in the analysis were efficacy, adverse effects, cost, and adherence, with relative weights of 35%, 35%, 20%, and 10%, respectively. For each agent, attribute scores were calculated, weighted, and then summed to generate a total utility score. The agent with the highest total utility score was considered the preferred agent. Aripiprazole, with a total utility score of 75.8, was the alternative agent with the highest total utility score in this model. This was followed by ziprasidone, risperidone, and quetiapine, with total utility scores of 71.8, 69.0, and 65.9, respectively. Olanzapine received the lowest total utility score. A sensitivity analysis was performed and failed to displace aripiprazole as the agent with the highest total utility score. This model suggests that aripiprazole should be considered a preferred agent for the treatment of schizophrenia unless found to be otherwise inappropriate.

Comparative SWOT analysis of strategic environmental assessment systems in the Middle East and North Africa region.

PubMed

Rachid, G; El Fadel, M

2013-08-15

This paper presents a SWOT analysis of SEA systems in the Middle East North Africa region through a comparative examination of the status, application and structure of existing systems based on country-specific legal, institutional and procedural frameworks. The analysis is coupled with the multi-attribute decision making method (MADM) within an analytical framework that involves both performance analysis based on predefined evaluation criteria and countries' self-assessment of their SEA system through open-ended surveys. The results show heterogenous status with a general delayed progress characterized by varied levels of weaknesses embedded in the legal and administrative frameworks and poor integration with the decision making process. Capitalizing on available opportunities, the paper highlights measures to enhance the development and enactment of SEA in the region. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Response-Time Approach to Comparing Generalized Rational and Take-the-Best Models of Decision Making

ERIC Educational Resources Information Center

Bergert, F. Bryan; Nosofsky, Robert M.

2007-01-01

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT)…

Multiattribute evaluation of regional cotton variety trials.

PubMed

Basford, K E; Kroonenberg, P M; Delacy, I H; Lawrence, P K

1990-02-01

The Australian Cotton Cultivar Trials (ACCT) are designed to investigate various cotton [Gossypium hirsutum (L.)] lines in several locations in New South Wales and Queensland each year. If these lines are to be assessed by the simultaneous use of yield and lint quality data, then a multivariate technique applicable to three-way data is desirable. Two such techniques, the mixture maximum likelihood method of clustering and three-mode principal component analysis, are described and used to analyze these data. Applied together, the methods enhance each other's usefulness in interpreting the information on the line response patterns across the locations. The methods provide a good integration of the responses across environments of the entries for the different attributes in the trials. For instance, using yield as the sole criterion, the excellence of the namcala and coker group for quality is overlooked. The analyses point to a decision in favor of either high yields of moderate to good quality lint or moderate yield but superior lint quality. The decisions indicated by the methods confirmed the selections made by the plant breeders. The procedures provide a less subjective, relatively easy to apply and interpret analytical method of describing the patterns of performance and associations in complex multiattribute and multilocation trials. This should lead to more efficient selection among lines in such trials.

Decision-making in irrigation networks: Selecting appropriate canal structures using multi-attribute decision analysis.

PubMed

Hosseinzade, Zeinab; Pagsuyoin, Sheree A; Ponnambalam, Kumaraswamy; Monem, Mohammad J

2017-12-01

The stiff competition for water between agriculture and non-agricultural production sectors makes it necessary to have effective management of irrigation networks in farms. However, the process of selecting flow control structures in irrigation networks is highly complex and involves different levels of decision makers. In this paper, we apply multi-attribute decision making (MADM) methodology to develop a decision analysis (DA) framework for evaluating, ranking and selecting check and intake structures for irrigation canals. The DA framework consists of identifying relevant attributes for canal structures, developing a robust scoring system for alternatives, identifying a procedure for data quality control, and identifying a MADM model for the decision analysis. An application is illustrated through an analysis for automation purposes of the Qazvin irrigation network, one of the oldest and most complex irrigation networks in Iran. A survey questionnaire designed based on the decision framework was distributed to experts, managers, and operators of the Qazvin network and to experts from the Ministry of Power in Iran. Five check structures and four intake structures were evaluated. A decision matrix was generated from the average scores collected from the survey, and was subsequently solved using TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. To identify the most critical structure attributes for the selection process, optimal attribute weights were calculated using Entropy method. For check structures, results show that the duckbill weir is the preferred structure while the pivot weir is the least preferred. Use of the duckbill weir can potentially address the problem with existing Amil gates where manual intervention is required to regulate water levels during periods of flow extremes. For intake structures, the Neyrpic® gate and constant head orifice are the most and least preferred alternatives, respectively. Some advantages of the Neyrpic® gate are ease of operation and capacity to measure discharge flows. Overall, the application to the Qazvin irrigation network demonstrates the utility of the proposed DA framework in selecting appropriate structures for regulating water flows in irrigation canals. This framework systematically aids the decision process by capturing decisions made at various levels (individual farmers to high-level management). It can be applied to other cases where a new irrigation network is being designed, or where changes in irrigation structures need to be identified to improve flow control in existing networks. Copyright © 2017 Elsevier B.V. All rights reserved.

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education.

PubMed

Phelps, Charles; Madhavan, Guruprasad; Rappuoli, Rino; Levin, Scott; Shortliffe, Edward; Colwell, Rita

2016-03-01

Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost-effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Our work employed a multicriteria systems analysis approach--specifically, multiattribute utility theory--to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost-effectiveness analysis approach. (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost-effectiveness analysis. (2) More sophisticated systems-level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost-effectiveness analysis. The Strategic Multi-Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. © 2016 Milbank Memorial Fund.

Risk-based decision making for terrorism applications.

PubMed

Dillon, Robin L; Liebe, Robert M; Bestafka, Thomas

2009-03-01

This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.

National Drug Formulary review of statin therapeutic group using the multiattribute scoring tool

PubMed Central

Ramli, Azuana; Aljunid, Syed Mohamed; Sulong, Saperi; Md Yusof, Faridah Aryani

2013-01-01

Purpose HMG-CoA reductase inhibitors (statins) are extensively used in treating hypercholesterolemia. The statins available in Malaysia include atorvastatin, lovastatin, pravastatin, rosuvastatin, simvastatin, and fluvastatin. Over the years, they have accumulated in the National Drug Formulary; hence, the need for review. Effective selection of the best drugs to remain in the formulary can become complex due to the multiple drug attributes involved, and is made worse by the limited time and resources available. The multiattribute scoring tool (MAST) systematizes the evaluation of the drug attributes to facilitate the drug selection process. In this study, a MAST framework was developed to rank the statins based on their utilities or benefits. Methods Published literature on multicriteria decision analysis (MCDA) were studied and five sessions of expert group discussions were conducted to build the MAST framework and to review the evidence. The attributes identified and selected for analysis were efficacy (clinical efficacy, clinical endpoints), safety (drug interactions, serious side effects and documentation), drug applicability (drug strength/formulation, indications, dose frequency, side effects, food–drug interactions, and dose adjustments), and cost. The average weights assigned by the members for efficacy, safety, drug applicability and cost were 32.6%, 26.2%, 24.1%, and 17.1%, respectively. The utility values of the attributes were scored based on the published evidence or/and agreements during the group discussions. The attribute scores were added up to provide the total utility score. Results Using the MAST, the six statins under review were successfully scored and ranked. Atorvastatin scored the highest total utility score (TUS) of 84.48, followed by simvastatin (83.11). Atorvastatin and simvastatin scored consistently high, even before drug costs were included. The low scores on the side effects for atorvastatin were compensated for by the higher scores on the clinical endpoints resulting in a higher TUS for atorvastatin. Fluvastatin recorded the lowest TUS. Conclusion The multiattribute scoring tool was successfully applied to organize decision variables in reviewing statins for the formulary. Based on the TUS, atorvastatin is recommended to remain in the formulary and be considered as first-line in the treatment of hypercholesterolemia. PMID:24353428

Research of Simple Multi-Attribute Rating Technique for Decision Support

NASA Astrophysics Data System (ADS)

Siregar, Dodi; Arisandi, Diki; Usman, Ari; Irwan, Dedy; Rahim, Robbi

2017-12-01

One of the roles of decision support system is that it can assist the decision maker in obtaining the appropriate alternative with the desired criteria, one of the methods that could apply for the decision maker is SMART method with multicriteria decision making. This multi-criteria decision-making theory has meaning where every alternative has criteria and has value and weight, and the author uses this approach to facilitate decision making with a compelling case. The problems discussed in this paper are classified into problems of a variety Multiobjective (multiple goals to be accomplished) and multicriteria (many of the decisive criteria in reaching such decisions).

Spaceborne power systems preference analyses. Volume 2: Decision analysis

NASA Technical Reports Server (NTRS)

Smith, J. H.; Feinberg, A.; Miles, R. F., Jr.

1985-01-01

Sixteen alternative spaceborne nuclear power system concepts were ranked using multiattribute decision analysis. The purpose of the ranking was to identify promising concepts for further technology development and the issues associated with such development. Four groups were interviewed to obtain preference. The four groups were: safety, systems definition and design, technology assessment, and mission analysis. The highest ranked systems were the heat-pipe thermoelectric systems, heat-pipe Stirling, in-core thermionic, and liquid-metal thermoelectric systems. The next group contained the liquid-metal Stirling, heat-pipe Alkali Metal Thermoelectric Converter (AMTEC), heat-pipe Brayton, liquid-metal out-of-core thermionic, and heat-pipe Rankine systems. The least preferred systems were the liquid-metal AMTEC, heat-pipe thermophotovoltaic, liquid-metal Brayton and Rankine, and gas-cooled Brayton. The three nonheat-pipe technologies selected matched the top three nonheat-pipe systems ranked by this study.

Prioritization of highway maintenance functions using multi-attribute decision making with fuzzy pairwise comparison.

DOT National Transportation Integrated Search

2011-09-01

"As is the case for most of the Departments of Transportation in the U.S., the Texas Department of : Transportation has been experiencing fluctuations of budget for maintaining and preserving its highway : infrastructure over the recent years. If the...

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop.

PubMed

Li, Lian-Hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

PubMed Central

Li, Lian-hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility. PMID:26414758

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

PubMed

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

Integrated continuous bioprocessing: Economic, operational, and environmental feasibility for clinical and commercial antibody manufacture.

PubMed

Pollock, James; Coffman, Jon; Ho, Sa V; Farid, Suzanne S

2017-07-01

This paper presents a systems approach to evaluating the potential of integrated continuous bioprocessing for monoclonal antibody (mAb) manufacture across a product's lifecycle from preclinical to commercial manufacture. The economic, operational, and environmental feasibility of alternative continuous manufacturing strategies were evaluated holistically using a prototype UCL decisional tool that integrated process economics, discrete-event simulation, environmental impact analysis, operational risk analysis, and multiattribute decision-making. The case study focused on comparing whole bioprocesses that used either batch, continuous or a hybrid combination of batch and continuous technologies for cell culture, capture chromatography, and polishing chromatography steps. The cost of goods per gram (COG/g), E-factor, and operational risk scores of each strategy were established across a matrix of scenarios with differing combinations of clinical development phase and company portfolio size. The tool outputs predict that the optimal strategy for early phase production and small/medium-sized companies is the integrated continuous strategy (alternating tangential flow filtration (ATF) perfusion, continuous capture, continuous polishing). However, the top ranking strategy changes for commercial production and companies with large portfolios to the hybrid strategy with fed-batch culture, continuous capture and batch polishing from a COG/g perspective. The multiattribute decision-making analysis highlighted that if the operational feasibility was considered more important than the economic benefits, the hybrid strategy would be preferred for all company scales. Further considerations outside the scope of this work include the process development costs required to adopt continuous processing. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:854-866, 2017. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

Decision analysis for a data collection system of patient-controlled analgesia with a multi-attribute utility model.

PubMed

Lee, I-Jung; Huang, Shih-Yu; Tsou, Mei-Yung; Chan, Kwok-Hon; Chang, Kuang-Yi

2010-10-01

Data collection systems are very important for the practice of patient-controlled analgesia (PCA). This study aimed to evaluate 3 PCA data collection systems and selected the most favorable system with the aid of multiattribute utility (MAU) theory. We developed a questionnaire with 10 items to evaluate the PCA data collection system and 1 item for overall satisfaction based on MAU theory. Three systems were compared in the questionnaire, including a paper record, optic card reader and personal digital assistant (PDA). A pilot study demonstrated a good internal and test-retest reliability of the questionnaire. A weighted utility score combining the relative importance of individual items assigned by each participant and their responses to each question was calculated for each system. Sensitivity analyses with distinct weighting protocols were conducted to evaluate the stability of the final results. Thirty potential users of a PCA data collection system were recruited in the study. The item "easy to use" had the highest median rank and received the heaviest mean weight among all items. MAU analysis showed that the PDA system had a higher utility score than that in the other 2 systems. Sensitivity analyses revealed that both inverse and reciprocal weighting processes favored the PDA system. High correlations between overall satisfaction and MAU scores from miscellaneous weighting protocols suggested a good predictive validity of our MAU-based questionnaire. The PDA system was selected as the most favorable PCA data collection system by the MAU analysis. The item "easy to use" was the most important attribute of the PCA data collection system. MAU theory can evaluate alternatives by taking into account individual preferences of stakeholders and aid in better decision-making. Copyright © 2010 Elsevier. Published by Elsevier B.V. All rights reserved.

Beyond utilitarianism: a method for analyzing competing ethical principles in a decision analysis of liver transplantation.

PubMed

Volk, Michael L; Lok, Anna S F; Ubel, Peter A; Vijan, Sandeep

2008-01-01

The utilitarian foundation of decision analysis limits its usefulness for many social policy decisions. In this study, the authors examine a method to incorporate competing ethical principles in a decision analysis of liver transplantation for a patient with acute liver failure (ALF). A Markov model was constructed to compare the benefit of transplantation for a patient with ALF versus the harm caused to other patients on the waiting list and to determine the lowest acceptable 5-y posttransplant survival for the ALF patient. The weighting of the ALF patient and other patients was then adjusted using a multiattribute variable incorporating utilitarianism, urgency, and other principles such as fair chances. In the base-case analysis, the strategy of transplanting the ALF patient resulted in a 0.8% increase in the risk of death and a utility loss of 7.8 quality-adjusted days of life for each of the other patients on the waiting list. These harms cumulatively outweighed the benefit of transplantation for an ALF patient having a posttransplant survival of less than 48% at 5 y. However, the threshold for an acceptable posttransplant survival for the ALF patient ranged from 25% to 56% at 5 y, depending on the ethical principles involved. The results of the decision analysis vary depending on the ethical perspective. This study demonstrates how competing ethical principles can be numerically incorporated in a decision analysis.

Deciding how to decide: ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making.

PubMed

Fellows, Lesley K

2006-04-01

Ventromedial frontal lobe (VMF) damage is associated with impaired decision making. Recent efforts to understand the functions of this brain region have focused on its role in tracking reward, punishment and risk. However, decision making is complex, and frontal lobe damage might be expected to affect it at other levels. This study used process-tracing techniques to explore the effect of VMF damage on multi-attribute decision making under certainty. Thirteen subjects with focal VMF damage were compared with 11 subjects with frontal damage that spared the VMF and 21 demographically matched healthy control subjects. Participants chose rental apartments in a standard information board task drawn from the literature on normal decision making. VMF subjects performed the decision making task in a way that differed markedly from all other groups, favouring an 'alternative-based' information acquisition strategy (i.e. they organized their information search around individual apartments). In contrast, both healthy control subjects and subjects with damage predominantly involving dorsal and/or lateral prefrontal cortex pursued primarily 'attribute-based' search strategies (in which information was acquired about categories such as rent and noise level across several apartments). This difference in the pattern of information acquisition argues for systematic differences in the underlying decision heuristics and strategies employed by subjects with VMF damage, which in turn may affect the quality of their choices. These findings suggest that the processes supported by ventral and medial prefrontal cortex need to be conceptualized more broadly, to account for changes in decision making under conditions of certainty, as well as uncertainty, following damage to these areas.

Integrated seismic stochastic inversion and multi-attributes to delineate reservoir distribution: Case study MZ fields, Central Sumatra Basin

NASA Astrophysics Data System (ADS)

Haris, A.; Novriyani, M.; Suparno, S.; Hidayat, R.; Riyanto, A.

2017-07-01

This study presents the integration of seismic stochastic inversion and multi-attributes for delineating the reservoir distribution in term of lithology and porosity in the formation within depth interval between the Top Sihapas and Top Pematang. The method that has been used is a stochastic inversion, which is integrated with multi-attribute seismic by applying neural network Probabilistic Neural Network (PNN). Stochastic methods are used to predict the probability mapping sandstone as the result of impedance varied with 50 realizations that will produce a good probability. Analysis of Stochastic Seismic Tnversion provides more interpretive because it directly gives the value of the property. Our experiment shows that AT of stochastic inversion provides more diverse uncertainty so that the probability value will be close to the actual values. The produced AT is then used for an input of a multi-attribute analysis, which is used to predict the gamma ray, density and porosity logs. To obtain the number of attributes that are used, stepwise regression algorithm is applied. The results are attributes which are used in the process of PNN. This PNN method is chosen because it has the best correlation of others neural network method. Finally, we interpret the product of the multi-attribute analysis are in the form of pseudo-gamma ray volume, density volume and volume of pseudo-porosity to delineate the reservoir distribution. Our interpretation shows that the structural trap is identified in the southeastern part of study area, which is along the anticline.

Decision-making Strategies and Performance among Seniors1

PubMed Central

Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

2011-01-01

Using paper and pencil experiments administered in senior centers, we examine decision-making performance in multi-attribute decision problems. We differentiate the effects of declining cognitive performance and changing cognitive process on decision-making performance of seniors as they age. We find a significant decline in performance with age due to reduced reliance on common heuristics and increased decision-making randomness among our oldest subjects. However, we find that increasing the number of options in a decision problem increases the number of heuristics brought to the task. This challenges the choice overload view that people give up when confronted with too much choice. PMID:22408282

Multi-criteria decision analysis in environmental sciences: ten years of applications and trends.

PubMed

Huang, Ivy B; Keisler, Jeffrey; Linkov, Igor

2011-09-01

Decision-making in environmental projects requires consideration of trade-offs between socio-political, environmental, and economic impacts and is often complicated by various stakeholder views. Multi-criteria decision analysis (MCDA) emerged as a formal methodology to face available technical information and stakeholder values to support decisions in many fields and can be especially valuable in environmental decision making. This study reviews environmental applications of MCDA. Over 300 papers published between 2000 and 2009 reporting MCDA applications in the environmental field were identified through a series of queries in the Web of Science database. The papers were classified by their environmental application area, decision or intervention type. In addition, the papers were also classified by the MCDA methods used in the analysis (analytic hierarchy process, multi-attribute utility theory, and outranking). The results suggest that there is a significant growth in environmental applications of MCDA over the last decade across all environmental application areas. Multiple MCDA tools have been successfully used for environmental applications. Even though the use of the specific methods and tools varies in different application areas and geographic regions, our review of a few papers where several methods were used in parallel with the same problem indicates that recommended course of action does not vary significantly with the method applied. Published by Elsevier B.V.

Selecting the Best Thermal Building Insulation Using a Multi-Attribute Decision Model

DTIC Science & Technology

2008-03-01

materials which come in various forms. Rock wool, also called mineral wool , is made from natural minerals and was developed in the mid-1800s (NAIMA...2008). Fiberglass is a form of mineral wool and accounts for approximately 85% of the market for residential insulation. Synthetic insulating

Goal Expectations as Predictors of Retirement Intentions

ERIC Educational Resources Information Center

Brougham, Ruby R.; Walsh, David A.

2005-01-01

The current study explored the contribution of personal goals to retirement decisions. A SMARTER methodology (to assess multiattribute utility) and taxonomy of human goals were used to investigate the relationship between older workers' personal goals and their retirement intentions. Two hundred and fifty-one employees of a large university,…

Modeling recreation participants' willingness to substitute using multi-attribute indicators

Treesearch

Yung-Ping (Emilio) Tseng; Robert B. Ditton

2008-01-01

A logistic regression was used to predict anglers' resource-substitution decisions based on three dimensions of recreation specialization (behavior, skill and knowledge, and commitment), two dimensions of place attachment (place identity and place dependence), and three demographic indicators. Results indicated that place dependence was the most effective...

Trusted Advisors, Decision Models and Other Keys to Communicating Science to Decision Makers

NASA Astrophysics Data System (ADS)

Webb, E.

2006-12-01

Water resource management decisions often involve multiple parties engaged in contentious negotiations that try to navigate through complex combinations of legal, social, hydrologic, financial, and engineering considerations. The standard approach for resolving these issues is some form of multi-party negotiation, a formal court decision, or a combination of the two. In all these cases, the role of the decision maker(s) is to choose and implement the best option that fits the needs and wants of the community. However, each path to a decision carries the risk of technical and/or financial infeasibility as well as the possibility of unintended consequences. To help reduce this risk, decision makers often rely on some type of predictive analysis from which they can evaluate the projected consequences of their decisions. Typically, decision makers are supported in the analysis process by trusted advisors who engage in the analysis as well as the day to day tasks associated with multi-party negotiations. In the case of water resource management, the analysis is frequently a numerical model or set of models that can simulate various management decisions across multiple systems and output results that illustrate the impact on areas of concern. Thus, in order to communicate scientific knowledge to the decision makers, the quality of the communication between the analysts, the trusted advisor, and the decision maker must be clear and direct. To illustrate this concept, a multi-attribute decision analysis matrix will be used to outline the value of computer model-based collaborative negotiation approaches to guide water resources decision making and communication with decision makers. In addition, the critical role of the trusted advisor and other secondary participants in the decision process will be discussed using examples from recent water negotiations.

Decision-theoretic methodology for reliability and risk allocation in nuclear power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, N.Z.; Papazoglou, I.A.; Bari, R.A.

1985-01-01

This paper describes a methodology for allocating reliability and risk to various reactor systems, subsystems, components, operations, and structures in a consistent manner, based on a set of global safety criteria which are not rigid. The problem is formulated as a multiattribute decision analysis paradigm; the multiobjective optimization, which is performed on a PRA model and reliability cost functions, serves as the guiding principle for reliability and risk allocation. The concept of noninferiority is used in the multiobjective optimization problem. Finding the noninferior solution set is the main theme of the current approach. The assessment of the decision maker's preferencesmore » could then be performed more easily on the noninferior solution set. Some results of the methodology applications to a nontrivial risk model are provided and several outstanding issues such as generic allocation and preference assessment are discussed.« less

Comparison of potential method in analytic hierarchy process for multi-attribute of catering service companies

NASA Astrophysics Data System (ADS)

Mamat, Siti Salwana; Ahmad, Tahir; Awang, Siti Rahmah

2017-08-01

Analytic Hierarchy Process (AHP) is a method used in structuring, measuring and synthesizing criteria, in particular ranking of multiple criteria in decision making problems. On the other hand, Potential Method is a ranking procedure in which utilizes preference graph ς (V, A). Two nodes are adjacent if they are compared in a pairwise comparison whereby the assigned arc is oriented towards the more preferred node. In this paper Potential Method is used to solve problem on a catering service selection. The comparison of result by using Potential method is made with Extent Analysis. The Potential Method is found to produce the same rank as Extent Analysis in AHP.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

PubMed Central

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541

Preference Reversal in Multiattribute Choice

ERIC Educational Resources Information Center

Tsetsos, Konstantinos; Usher, Marius; Chater, Nick

2010-01-01

A central puzzle for theories of choice is that people's preferences between options can be reversed by the presence of decoy options (that are not chosen) or by the presence of other irrelevant options added to the choice set. Three types of reversal effect reported in the decision-making literature, the attraction, compromise, and similarity…

Postscript: Contrasting Predictions for Preference Reversal

ERIC Educational Resources Information Center

Usher, Marius; Tsetsos, Konstantinos; Chater, Nick

2010-01-01

In this post scrit, the authors discuss an article by Hotaling, Busemeyer, and Li which provided a valuable reply to the challenges the current authors raised for the decision field theory (DFT) account of preference reversal in multiattribute choice. They agree with Hotaling, Busemeyer, and Li's observation that with the addition of an internal…

Rank Weighting in Multiattribute Utility Decision Making: Avoiding the Pitfalls of Equal Weights.

DTIC Science & Technology

1979-09-01

set change are discussed in relation to the conditions of Wainer’s (Wainer, 1976) ’ equal weights theorem’ and the resulting sensitivity to weighting of...as equal weights. Rank weighting of importance dimensions demonstrate marked improvement of approximation as reflected in both Pearson and rank order

Choice and explanation in medical management: a multiattribute model of artificial intelligence approaches.

PubMed

Rennels, G D; Shortliffe, E H; Miller, P L

1987-01-01

This paper explores a model of choice and explanation in medical management and makes clear its advantages and limitations. The model is based on multiattribute decision making (MADM) and consists of four distinct strategies for choice and explanation, plus combinations of these four. Each strategy is a restricted form of the general MADM approach, and each makes restrictive assumptions about the nature of the domain. The advantage of tailoring a restricted form of a general technique to a particular domain is that such efforts may better capture the character of the domain and allow choice and explanation to be more naturally modelled. The uses of the strategies for both choice and explanation are illustrated with analyses of several existing medical management artificial intelligence (AI) systems, and also with examples from the management of primary breast cancer. Using the model it is possible to identify common underlying features of these AI systems, since each employs portions of this model in different ways. Thus the model enables better understanding and characterization of the seemingly ad hoc decision making of previous systems.

Application of multiattribute decision-making methods for the determination of relative significance factor of impact categories.

PubMed

Noh, Jaesung; Lee, Kun Mo

2003-05-01

A relative significance factor (f(i)) of an impact category is the external weight of the impact category. The objective of this study is to propose a systematic and easy-to-use method for the determination of f(i). Multiattribute decision-making (MADM) methods including the analytical hierarchy process (AHP), the rank-order centroid method, and the fuzzy method were evaluated for this purpose. The results and practical aspects of using the three methods are compared. Each method shows the same trend, with minor differences in the value of f(i). Thus, all three methods can be applied to the determination of f(i). The rank order centroid method reduces the number of pairwise comparisons by placing the alternatives in order, although it has inherent weakness over the fuzzy method in expressing the degree of vagueness associated with assigning weights to criteria and alternatives. The rank order centroid method is considered a practical method for the determination of f(i) because it is easier and simpler to use compared to the AHP and the fuzzy method.

Auditory attention and multiattribute decision-making during a 33 h sleep-deprivation period: mean performance and between-subject dispersions.

PubMed

Linde, L; Edland, A; Bergström, M

1999-05-01

One purpose of this study was to compare attention in the evening (22:00 h), in the late night (04:00 h), in the morning (10:00 h) and in the afternoon (16:00 h) during a period of complete wakefulness beginning at 08:00 h with a mean daytime performance without sleep deprivation. Another purpose was to investigate sleep deprivation effects on a multi-attribute decision-making task with and without time pressure. Twelve sleep-deprived male students were compared with 12 male non-sleep-deprived students. Both groups were tested five times with an auditory attention and a symbol coding task. Significant declines (p < 0.05) in mean level of performance on the auditory attention task were found at 04:00, 10:00 and 16:00 h for subjects forced to the vigil. However, the effect of the sleep deprivation manifested itself even more in increased between-subject dispersions. There were no differences between time pressure and no time pressure on the decision-making task and no significant differences between sleep-deprived and non-sleep-deprived subjects in decision strategies. In fact, the pattern of decision strategies among the sleep-deprived subject was more similar to a pattern of decision strategies typical for non-stressful conditions than the pattern of decision strategies among the non-sleep-deprived subjects. This result may have been due to the fact that the sleep loss acted as a dearouser. Here too, however, the variances differed significantly among sleep-deprived and non-sleep-deprived subjects, indicating that the sleep-deprived subjects were more variable in their decision strategy pattern than the control group.

Using multiple pharmacoeconomic methods to conduct a cost-effectiveness analysis of histamine H2-receptor antagonists.

PubMed

McCoy, S; Blayney-Chandramouli, J; Mutnick, A

1998-12-15

A formulary decision at a health care institution was studied by using two pharmacoeconomic methods. A pharmacoeconomic study was undertaken to assess the impact of a 1995 formulary decision to designate cimetidine as the primary histamine H2-receptor antagonist (H2RA) and to restrict the use of famotidine. Consecutive patients receiving either i.v. cimetidine or famotidine for stress ulcer prophylaxis were reviewed during a two-month period in 1997, and information on demographics, dosage and duration of H2RA therapy, admission date, laboratory test values, and adverse drug reactions was collected. Data for 62 patients (43 cimetidine recipients and 19 famotidine recipients) were evaluated. Therapy was categorized as successful or failed, and the data were then evaluated by decision analysis to evaluate the cost-effectiveness of the agents and by multiattribute utility theory (MAUT) to incorporate a humanistic evaluation of the treatments, namely, the number of doses administered and the number of times dosages were changed. The decision tree revealed that the average cost of receiving cimetidine was $82.01 and the average cost of famotidine therapy was $92.45. The MAUT analysis showed that cimetidine was the preferred agent as long as cost was valued at greater than 60% of the decision-making process and efficacy remained equal between the two agents. Two pharmacoeconomic methods lent support to a formulary decision at a health care institution.

Zoning of an agricultural field using a fuzzy indicator model in combination with tool for multi-attributed decision-making

USDA-ARS?s Scientific Manuscript database

Zoning of agricultural fields is an important task for utilization of precision farming technology. This paper extends previously published work entitled “Zoning of an agricultural field using a fuzzy indicator model” to a general case where there is disagreement between groups of managers or expert...

Augmenting the Deliberative Method for Ranking Risks.

PubMed

Susel, Irving; Lasley, Trace; Montezemolo, Mark; Piper, Joel

2016-01-01

The Department of Homeland Security (DHS) characterized and prioritized the physical cross-border threats and hazards to the nation stemming from terrorism, market-driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top-ranked and bottom-ranked risks, let alone deciding what the stand-out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand-out risks to help prioritize further analysis. © 2015 Society for Risk Analysis.

A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

NASA Astrophysics Data System (ADS)

Zhang, Wancheng; Xu, Yejun; Wang, Huimin

2016-01-01

The aim of this paper is to put forward a consensus reaching method for multi-attribute group decision-making (MAGDM) problems with linguistic information, in which the weight information of experts and attributes is unknown. First, some basic concepts and operational laws of 2-tuple linguistic label are introduced. Then, a grey relational analysis method and a maximising deviation method are proposed to calculate the incomplete weight information of experts and attributes respectively. To eliminate the conflict in the group, a weight-updating model is employed to derive the weights of experts based on their contribution to the consensus reaching process. After conflict elimination, the final group preference can be obtained which will give the ranking of the alternatives. The model can effectively avoid information distortion which is occurred regularly in the linguistic information processing. Finally, an illustrative example is given to illustrate the application of the proposed method and comparative analysis with the existing methods are offered to show the advantages of the proposed method.

Hierarchical competitions subserving multi-attribute choice

PubMed Central

Hunt, Laurence T; Dolan, Raymond J; Behrens, Timothy EJ

2015-01-01

Valuation is a key tenet of decision neuroscience, where it is generally assumed that different attributes of competing options are assimilated into unitary values. Such values are central to current neural models of choice. By contrast, psychological studies emphasize complex interactions between choice and valuation. Principles of neuronal selection also suggest competitive inhibition may occur in early valuation stages, before option selection. Here, we show behavior in multi-attribute choice is best explained by a model involving competition at multiple levels of representation. This hierarchical model also explains neural signals in human brain regions previously linked to valuation, including striatum, parietal and prefrontal cortex, where activity represents competition within-attribute, competition between attributes, and option selection. This multi-layered inhibition framework challenges the assumption that option values are computed before choice. Instead our results indicate a canonical competition mechanism throughout all stages of a processing hierarchy, not simply at a final choice stage. PMID:25306549

Decision Support for Personalized Cloud Service Selection through Multi-Attribute Trustworthiness Evaluation

PubMed Central

Ding, Shuai; Xia, Chen-Yi; Zhou, Kai-Le; Yang, Shan-Lin; Shang, Jennifer S.

2014-01-01

Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer. Many existing models cannot easily deal with cloud services which have very few historical records. In this paper, we propose a novel service selection approach in which the missing value prediction and the multi-attribute trustworthiness evaluation are commonly taken into account. By simply collecting limited historical records, the current approach is able to support the personalized trustworthy service selection. The experimental results also show that our approach performs much better than other competing ones with respect to the customer preference and expectation in trustworthiness assessment. PMID:24972237

Decision support for personalized cloud service selection through multi-attribute trustworthiness evaluation.

PubMed

Ding, Shuai; Xia, Cheng-Yi; Xia, Chen-Yi; Zhou, Kai-Le; Yang, Shan-Lin; Shang, Jennifer S

2014-01-01

Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer. Many existing models cannot easily deal with cloud services which have very few historical records. In this paper, we propose a novel service selection approach in which the missing value prediction and the multi-attribute trustworthiness evaluation are commonly taken into account. By simply collecting limited historical records, the current approach is able to support the personalized trustworthy service selection. The experimental results also show that our approach performs much better than other competing ones with respect to the customer preference and expectation in trustworthiness assessment.

Visual analytics techniques for large multi-attribute time series data

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.

2008-01-01

Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year's monthly sales with last year's sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need to detect the outliers early enough to act upon them. In this paper, two new visual analytic techniques are introduced: The color cell-based Visual Time Series Line Charts and Maps highlight significant changes over time in a long time series data and the new Visual Content Query facilitates finding the contents and histories of interesting patterns and anomalies, which leads to root cause identification. We have applied both methods to two real-world applications to mine enterprise data warehouse and customer credit card fraud data to illustrate the wide applicability and usefulness of these techniques.

The eyes have it: Using eye tracking to inform information processing strategies in multi-attributes choices.

PubMed

Ryan, Mandy; Krucien, Nicolas; Hermens, Frouke

2018-04-01

Although choice experiments (CEs) are widely applied in economics to study choice behaviour, understanding of how individuals process attribute information remains limited. We show how eye-tracking methods can provide insight into how decisions are made. Participants completed a CE, while their eye movements were recorded. Results show that although the information presented guided participants' decisions, there were also several processing biases at work. Evidence was found of (a) top-to-bottom, (b) left-to-right, and (c) first-to-last order biases. Experimental factors-whether attributes are defined as "best" or "worst," choice task complexity, and attribute ordering-also influence information processing. How individuals visually process attribute information was shown to be related to their choices. Implications for the design and analysis of CEs and future research are discussed. Copyright © 2017 John Wiley & Sons, Ltd.

Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews.

PubMed

Kuesten, Carla; Bi, Jian

2018-06-03

Conventional drivers of liking analysis was extended with a time dimension into temporal drivers of liking (TDOL) based on functional data analysis methodology and non-additive models for multiple-attribute time-intensity (MATI) data. The non-additive models, which consider both direct effects and interaction effects of attributes to consumer overall liking, include Choquet integral and fuzzy measure in the multi-criteria decision-making, and linear regression based on variance decomposition. Dynamics of TDOL, i.e., the derivatives of the relative importance functional curves were also explored. Well-established R packages 'fda', 'kappalab' and 'relaimpo' were used in the paper for developing TDOL. Applied use of these methods shows that the relative importance of MATI curves offers insights for understanding the temporal aspects of consumer liking for fruit chews.

"Geo-statistics methods and neural networks in geophysical applications: A case study"

NASA Astrophysics Data System (ADS)

Rodriguez Sandoval, R.; Urrutia Fucugauchi, J.; Ramirez Cruz, L. C.

2008-12-01

The study is focus in the Ebano-Panuco basin of northeastern Mexico, which is being explored for hydrocarbon reservoirs. These reservoirs are in limestones and there is interest in determining porosity and permeability in the carbonate sequences. The porosity maps presented in this study are estimated from application of multiattribute and neural networks techniques, which combine geophysics logs and 3-D seismic data by means of statistical relationships. The multiattribute analysis is a process to predict a volume of any underground petrophysical measurement from well-log and seismic data. The data consist of a series of target logs from wells which tie a 3-D seismic volume. The target logs are neutron porosity logs. From the 3-D seismic volume a series of sample attributes is calculated. The objective of this study is to derive a set of attributes and the target log values. The selected set is determined by a process of forward stepwise regression. The analysis can be linear or nonlinear. In the linear mode the method consists of a series of weights derived by least-square minimization. In the nonlinear mode, a neural network is trained using the select attributes as inputs. In this case we used a probabilistic neural network PNN. The method is applied to a real data set from PEMEX. For better reservoir characterization the porosity distribution was estimated using both techniques. The case shown a continues improvement in the prediction of the porosity from the multiattribute to the neural network analysis. The improvement is in the training and the validation, which are important indicators of the reliability of the results. The neural network showed an improvement in resolution over the multiattribute analysis. The final maps provide more realistic results of the porosity distribution.

Assessing the Reliability and Validity of Multi-Attribute Utility Procedures: An Application of the Theory of Generalizability

DTIC Science & Technology

1975-07-01

I WIWIHIHlipi pqpv<Hi^«^Rii.i ii mmw AD-A016 282 ASSESSING THE REALIBILITY AND VALIDITY OF MULTI-ATTRIBUTE UTILITY PROCEDURES: AN...more complicated and use data from actual experiments. Example 1: Analysis of raters making Importance judgments about attributes. In MAU studies...generaluablllty of JUDGE as contrasted to ÜASC. To do this, we win reanaIyze the data for each syste™ separately. This 1. valid since the initial

Can Carbon Nanomaterials Improve CZTS Photovoltaic Devices? Evaluation of Performance and Impacts Using Integrated Life-Cycle Assessment and Decision Analysis.

PubMed

Scott, Ryan P; Cullen, Alison C; Fox-Lent, Cate; Linkov, Igor

2016-10-01

In emergent photovoltaics, nanoscale materials hold promise for optimizing device characteristics; however, the related impacts remain uncertain, resulting in challenges to decisions on strategic investment in technology innovation. We integrate multi-criteria decision analysis (MCDA) and life-cycle assessment (LCA) results (LCA-MCDA) as a method of incorporating values of a hypothetical federal acquisition manager into the assessment of risks and benefits of emerging photovoltaic materials. Specifically, we compare adoption of copper zinc tin sulfide (CZTS) devices with molybdenum back contacts to alternative devices employing graphite or graphene instead of molybdenum. LCA impact results are interpreted alongside benefits of substitution including cost reductions and performance improvements through application of multi-attribute utility theory. To assess the role of uncertainty we apply Monte Carlo simulation and sensitivity analysis. We find that graphene or graphite back contacts outperform molybdenum under most scenarios and assumptions. The use of decision analysis clarifies potential advantages of adopting graphite as a back contact while emphasizing the importance of mitigating conventional impacts of graphene production processes if graphene is used in emerging CZTS devices. Our research further demonstrates that a combination of LCA and MCDA increases the usability of LCA in assessing product sustainability. In particular, this approach identifies the most influential assumptions and data gaps in the analysis and the areas in which either engineering controls or further data collection may be necessary. © 2016 Society for Risk Analysis.

Application of stochastic multiattribute analysis to assessment of single walled carbon nanotube synthesis processes.

PubMed

Canis, Laure; Linkov, Igor; Seager, Thomas P

2010-11-15

The unprecedented uncertainty associated with engineered nanomaterials greatly expands the need for research regarding their potential environmental consequences. However, decision-makers such as regulatory agencies, product developers, or other nanotechnology stakeholders may not find the results of such research directly informative of decisions intended to mitigate environmental risks. To help interpret research findings and prioritize new research needs, there is an acute need for structured decision-analytic aids that are operable in a context of extraordinary uncertainty. Whereas existing stochastic decision-analytic techniques explore uncertainty only in decision-maker preference information, this paper extends model uncertainty to technology performance. As an illustrative example, the framework is applied to the case of single-wall carbon nanotubes. Four different synthesis processes (arc, high pressure carbon monoxide, chemical vapor deposition, and laser) are compared based on five salient performance criteria. A probabilistic rank ordering of preferred processes is determined using outranking normalization and a linear-weighted sum for different weighting scenarios including completely unknown weights and four fixed-weight sets representing hypothetical stakeholder views. No single process pathway dominates under all weight scenarios, but it is likely that some inferior process technologies could be identified as low priorities for further research.

Decision Aids for Airborne Intercept Operations in Advanced Aircrafts

NASA Technical Reports Server (NTRS)

Madni, A.; Freedy, A.

1981-01-01

A tactical decision aid (TDA) for the F-14 aircrew, i.e., the naval flight officer and pilot, in conducting a multitarget attack during the performance of a Combat Air Patrol (CAP) role is presented. The TDA employs hierarchical multiattribute utility models for characterizing mission objectives in operationally measurable terms, rule based AI-models for tactical posture selection, and fast time simulation for maneuver consequence prediction. The TDA makes aspect maneuver recommendations, selects and displays the optimum mission posture, evaluates attackable and potentially attackable subsets, and recommends the 'best' attackable subset along with the required course perturbation.

Geographic Profiling: Knowledge Through Prediction

DTIC Science & Technology

2014-06-01

FTO Foreign Terrorist Organization GIS geographic information systems LE lawless elements MADM multi-attribute decision making MILF Moro Islamic...or her life. Anchor points can include the offender’s home , his or her workplace, a home of a friend of the offender, or even a bar or restaurant...more generally for the improvement of police patrols. In Memphis, TN, city officials have seen a decrease in crime with the help of operation Blue

Overall Performance Evaluation of Tubular Scraper Conveyors Using a TOPSIS-Based Multiattribute Decision-Making Method

PubMed Central

Yao, Yanping; Kou, Ziming; Meng, Wenjun; Han, Gang

2014-01-01

Properly evaluating the overall performance of tubular scraper conveyors (TSCs) can increase their overall efficiency and reduce economic investments, but such methods have rarely been studied. This study evaluated the overall performance of TSCs based on the technique for order of preference by similarity to ideal solution (TOPSIS). Three conveyors of the same type produced in the same factory were investigated. Their scraper space, material filling coefficient, and vibration coefficient of the traction components were evaluated. A mathematical model of the multiattribute decision matrix was constructed; a weighted judgment matrix was obtained using the DELPHI method. The linguistic positive-ideal solution (LPIS), the linguistic negative-ideal solution (LNIS), and the distance from each solution to the LPIS and the LNIS, that is, the approximation degrees, were calculated. The optimal solution was determined by ordering the approximation degrees for each solution. The TOPSIS-based results were compared with the measurement results provided by the manufacturer. The ordering result based on the three evaluated parameters was highly consistent with the result provided by the manufacturer. The TOPSIS-based method serves as a suitable evaluation tool for the overall performance of TSCs. It facilitates the optimal deployment of TSCs for industrial purposes. PMID:24991646

A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes

NASA Astrophysics Data System (ADS)

Lu, Hongwei; Ren, Lixia; Chen, Yizhong; Tian, Peipei; Liu, Jia

2017-12-01

Due to the uncertainty (i.e., fuzziness, stochasticity and imprecision) existed simultaneously during the process for groundwater remediation, the accuracy of ranking results obtained by the traditional methods has been limited. This paper proposes a cloud model based multi-attribute decision making framework (CM-MADM) with Monte Carlo for the contaminated-groundwater remediation strategies selection. The cloud model is used to handle imprecise numerical quantities, which can describe the fuzziness and stochasticity of the information fully and precisely. In the proposed approach, the contaminated concentrations are aggregated via the backward cloud generator and the weights of attributes are calculated by employing the weight cloud module. A case study on the remedial alternative selection for a contaminated site suffering from a 1,1,1-trichloroethylene leakage problem in Shanghai, China is conducted to illustrate the efficiency and applicability of the developed approach. Totally, an attribute system which consists of ten attributes were used for evaluating each alternative through the developed method under uncertainty, including daily total pumping rate, total cost and cloud model based health risk. Results indicated that A14 was evaluated to be the most preferred alternative for the 5-year, A5 for the 10-year, A4 for the 15-year and A6 for the 20-year remediation.

k-RP*{sub s}: A scalable distributed data structure for high-performance multi-attribute access

DOE Office of Scientific and Technical Information (OSTI.GOV)

Litwin, W.; Neimat, M.A.

k-RP*{sub s} is a new data structure for scalable multicomputer files with multi-attribute (k-d) keys. We discuss the k-RP*{sub s} file evolution and search algorithms. Performance analysis shows that a k-RP*{sub s} file can be much larger and orders of magnitude faster than a traditional k-d file. The speed-up is especially important for range and partial match searches that are often impractical with traditional k-d files. This opens up a new perspective for many applications.

A matter of tradeoffs: reintroduction as a multiple objective decision

USGS Publications Warehouse

Converse, Sarah J.; Moore, Clinton T.; Folk, Martin J.; Runge, Michael C.

2013-01-01

Decision making in guidance of reintroduction efforts is made challenging by the substantial scientific uncertainty typically involved. However, a less recognized challenge is that the management objectives are often numerous and complex. Decision makers managing reintroduction efforts are often concerned with more than just how to maximize the probability of reintroduction success from a population perspective. Decision makers are also weighing other concerns such as budget limitations, public support and/or opposition, impacts on the ecosystem, and the need to consider not just a single reintroduction effort, but conservation of the entire species. Multiple objective decision analysis is a powerful tool for formal analysis of such complex decisions. We demonstrate the use of multiple objective decision analysis in the case of the Florida non-migratory whooping crane reintroduction effort. In this case, the State of Florida was considering whether to resume releases of captive-reared crane chicks into the non-migratory whooping crane population in that state. Management objectives under consideration included maximizing the probability of successful population establishment, minimizing costs, maximizing public relations benefits, maximizing the number of birds available for alternative reintroduction efforts, and maximizing learning about the demographic patterns of reintroduced whooping cranes. The State of Florida engaged in a collaborative process with their management partners, first, to evaluate and characterize important uncertainties about system behavior, and next, to formally evaluate the tradeoffs between objectives using the Simple Multi-Attribute Rating Technique (SMART). The recommendation resulting from this process, to continue releases of cranes at a moderate intensity, was adopted by the State of Florida in late 2008. Although continued releases did not receive support from the International Whooping Crane Recovery Team, this approach does provide a template for the formal, transparent consideration of multiple, potentially competing, objectives in reintroduction decision making.

Integrated optimisation technique based on computer-aided capacity and safety evaluation for managing downstream lane-drop merging area of signalised junctions

NASA Astrophysics Data System (ADS)

Chen, CHAI; Yiik Diew, WONG

2017-02-01

This study provides an integrated strategy, encompassing microscopic simulation, safety assessment, and multi-attribute decision-making, to optimize traffic performance at downstream merging area of signalized intersections. A Fuzzy Cellular Automata (FCA) model is developed to replicate microscopic movement and merging behavior. Based on simulation experiment, the proposed FCA approach is able to provide capacity and safety evaluation of different traffic scenarios. The results are then evaluated through data envelopment analysis (DEA) and analytic hierarchy process (AHP). Optimized geometric layout and control strategies are then suggested for various traffic conditions. An optimal lane-drop distance that is dependent on traffic volume and speed limit can thus be established at the downstream merging area.

Identification of metrics to monitor salt marsh integrity on National Wildlife Refuges in relation to conservation and management objectives

USGS Publications Warehouse

Neckles, Hilary A.; Guntenspergen, Glenn R.; Shriver, W. George; Danz, Nicholas P.; Wiest, Whitney A.; Nagel, Jessica L.; Olker, Jennifer H.

2013-01-01

Implementation of these metrics for quantitative assessment of NWRS salt marsh integrity in FWS Region 5 requires developing sampling designs for each refuge. Additionally, it is important to determine how the monitoring information will be used within a management context. SDM should be used to complete the analysis of salt marsh management decisions. The next steps would involve 1) prioritizing and weighting the management objectives; 2) predicting responses to individual management actions in terms of objectives and metrics; 3) using multiattribute utility theory to convert all measurable attributes to a common utility scale; 4) determining the total management benefit of each action by summing utilities across objectives; and 5) maximizing the total management benefits within cost constraints for each refuge. This process would allow the optimum management decisions for NWRS salt marshes to be selected and implemented based directly on monitoring data and current understanding of marsh responses to management actions. Monitoring the outcome of management actions would then allow new monitoring data to be incorporated into subsequent decisions. 

Framing of task performance strategies: effects on performance in a multiattribute dynamic decision making environment.

PubMed

Nygren, T E

1997-09-01

It is well documented that the way a static choice task is "framed" can dramatically alter choice behavior, often leading to observable preference reversals. This framing effect appears to result from perceived changes in the nature or location of a person's initial reference point, but it is not clear how framing effects might generalize to performance on dynamic decision making tasks that are characterized by high workload, time constraints, risk, or stress. A study was conducted to examine the hypothesis that framing can introduce affective components to the decision making process and can influence, either favorably (positive frame) or adversely (negative frame), the implementation and use of decision making strategies in dynamic high-workload environments. Results indicated that negative frame participants were significantly impaired in developing and employing a simple optimal decision strategy relative to a positive frame group. Discussion focuses on implications of these results for models of dynamic decision making.

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale

PubMed Central

Diao, Yuzhu; Hu, Aqin

2018-01-01

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation. PMID:29498699

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

PubMed

Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

2018-03-02

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

Decision Making In Assignment Problem With Multiple Attributes Under Intuitionistic Fuzzy Environment

NASA Astrophysics Data System (ADS)

Mukherjee, Sathi; Basu, Kajla

2010-10-01

In this paper we develop a methodology to solve the multiple attribute assignment problems where the attributes are considered to be Intuitionistic Fuzzy Sets (IFS). We apply the concept of similarity measures of IFS to solve the Intuitionistic Fuzzy Multi-Attribute Assignment Problem (IFMAAP). The weights of the attributes are determined from expert opinion. An illustrative example is solved to verify the developed approach and to demonstrate its practicality.

Use of Influenza Risk Assessment Tool for Prepandemic Preparedness

PubMed Central

Trock, Susan C.

2018-01-01

In 2010, the Centers for Disease Control and Prevention began to develop an Influenza Risk Assessment Tool (IRAT) to methodically capture and assess information relating to influenza A viruses not currently circulating among humans. The IRAT uses a multiattribute, additive model to generate a summary risk score for each virus. Although the IRAT is not intended to predict the next pandemic influenza A virus, it has provided input into prepandemic preparedness decisions. PMID:29460739

Sustainability assessment of tertiary wastewater treatment technologies: a multi-criteria analysis.

PubMed

Plakas, K V; Georgiadis, A A; Karabelas, A J

2016-01-01

The multi-criteria analysis gives the opportunity to researchers, designers and decision-makers to examine decision options in a multi-dimensional fashion. On this basis, four tertiary wastewater treatment (WWT) technologies were assessed regarding their sustainability performance in producing recycled wastewater, considering a 'triple bottom line' approach (i.e. economic, environmental, and social). These are powdered activated carbon adsorption coupled with ultrafiltration membrane separation (PAC-UF), reverse osmosis, ozone/ultraviolet-light oxidation and heterogeneous photo-catalysis coupled with low-pressure membrane separation (photocatalytic membrane reactor, PMR). The participatory method called simple multi-attribute rating technique exploiting ranks was employed for assigning weights to selected sustainability indicators. This sustainability assessment approach resulted in the development of a composite index as a final metric, for each WWT technology evaluated. The PAC-UF technology appears to be the most appropriate technology, attaining the highest composite value regarding the sustainability performance. A scenario analysis confirmed the results of the original scenario in five out of seven cases. In parallel, the PMR was highlighted as the technology with the least variability in its performance. Nevertheless, additional actions and approaches are proposed to strengthen the objectivity of the final results.

A Stochastic Multi-Attribute Assessment of Energy Options for Fairbanks, Alaska

NASA Astrophysics Data System (ADS)

Read, L.; Madani, K.; Mokhtari, S.; Hanks, C. L.; Sheets, B.

2012-12-01

Many competing projects have been proposed to address Interior Alaska's high cost of energy—both for electricity production and for heating. Public and private stakeholders are considering the costs associated with these competing projects which vary in fuel source, subsidy requirements, proximity, and other factors. As a result, the current projects under consideration involve a complex cost structure of potential subsidies and reliance on present and future market prices, introducing a significant amount of uncertainty associated with each selection. Multi-criteria multi-decision making (MCMDM) problems of this nature can benefit from game theory and systems engineering methods, which account for behavior and preferences of stakeholders in the analysis to produce feasible and relevant solutions. This work uses a stochastic MCMDM framework to evaluate the trade-offs of each proposed project based on a complete cost analysis, environmental impact, and long-term sustainability. Uncertainty in the model is quantified via a Monte Carlo analysis, which helps characterize the sensitivity and risk associated with each project. Based on performance measures and criteria outlined by the stakeholders, a decision matrix will inform policy on selecting a project that is both efficient and preferred by the constituents.

Value-Based Assessment of New Medical Technologies: Towards a Robust Methodological Framework for the Application of Multiple Criteria Decision Analysis in the Context of Health Technology Assessment.

PubMed

Angelis, Aris; Kanavos, Panos

2016-05-01

In recent years, multiple criteria decision analysis (MCDA) has emerged as a likely alternative to address shortcomings in health technology assessment (HTA) by offering a more holistic perspective to value assessment and acting as an alternative priority setting tool. In this paper, we argue that MCDA needs to subscribe to robust methodological processes related to the selection of objectives, criteria and attributes in order to be meaningful in the context of healthcare decision making and fulfil its role in value-based assessment (VBA). We propose a methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outline the stages involved in each phase and discuss their relevance in the HTA process. Importantly, criteria and attributes need to satisfy a set of desired properties, otherwise the outcome of the analysis can produce spurious results and misleading recommendations. Assuming the methodological process we propose is adhered to, the application of MCDA presents three very distinct advantages to decision makers in the context of HTA and VBA: first, it acts as an instrument for eliciting preferences on the performance of alternative options across a wider set of explicit criteria, leading to a more complete assessment of value; second, it allows the elicitation of preferences across the criteria themselves to reflect differences in their relative importance; and, third, the entire process of preference elicitation can be informed by direct stakeholder engagement, and can therefore reflect their own preferences. All features are fully transparent and facilitate decision making.

Qualitatively Coherent Representation Makes Decision-Making Easier with Binary-Colored Multi-Attribute Tables: An Eye-Tracking Study

PubMed Central

Morii, Masahiro; Ideno, Takashi; Takemura, Kazuhisa; Okada, Mitsuhiro

2017-01-01

We aimed to identify the ways in which coloring cells affected decision-making in the context of binary-colored multi-attribute tables, using eye movement data. In our black-white attribute tables, the value of attributes was limited to two (with a certain threshold for each attribute) and each cell of the table was colored either black or white on the white background. We compared the two natural ways of systematic color assignment: “quantitatively coherent” ways and “qualitatively coherent” ways (namely, the ways in which the black-white distinction represented the quantitative amount distinction, and the ways in which the black-white distinction represented the quality distinction). The former consists of the following two types: (Type 1) “larger is black,” where the larger value-level was represented by black, and “smaller is white,” and (Type 2) “smaller is black.” The latter consisted of the following two types: (Type 3) “better is black,” and (Type 4) “worse is black.” We obtained the following two findings. [Result 1] The qualitatively coherent black-white tables (Types 3 and 4) made decision-making easier than the quantitatively coherent ones (Types 1 and 2). [Result 2] Among the two qualitatively coherent types, the “black is better” tables (Type 3) made decision making easier; in fact, the participants focused on the more important (black) cells in the case of “black is better” tables (Type 3) while they did not focus enough on the more important (white) ones in the case of the “white is better” tables (Type 4). We also examined some measures of eye movement patterns and showed that these measures supported our hypotheses. The data showed differences in the eye movement patterns between the first and second halves of each trial, which indicated the phased or combined decision strategies taken by the participants. PMID:28861020

Advanced GPR imaging of sedimentary features: integrated attribute analysis applied to sand dunes

NASA Astrophysics Data System (ADS)

Zhao, Wenke; Forte, Emanuele; Fontolan, Giorgio; Pipan, Michele

2018-04-01

We evaluate the applicability and the effectiveness of integrated GPR attribute analysis to image the internal sedimentary features of the Piscinas Dunes, SW Sardinia, Italy. The main objective is to explore the limits of GPR techniques to study sediment-bodies geometry and to provide a non-invasive high-resolution characterization of the different subsurface domains of dune architecture. On such purpose, we exploit the high-quality Piscinas data-set to extract and test different attributes of the GPR trace. Composite displays of multi-attributes related to amplitude, frequency, similarity and textural features are displayed with overlays and RGB mixed models. A multi-attribute comparative analysis is used to characterize different radar facies to better understand the characteristics of internal reflection patterns. The results demonstrate that the proposed integrated GPR attribute analysis can provide enhanced information about the spatial distribution of sediment bodies, allowing an enhanced and more constrained data interpretation.

Delineating chalk sand distribution of Ekofisk formation using probabilistic neural network (PNN) and stepwise regression (SWR): Case study Danish North Sea field

NASA Astrophysics Data System (ADS)

Haris, A.; Nafian, M.; Riyanto, A.

2017-07-01

Danish North Sea Fields consist of several formations (Ekofisk, Tor, and Cromer Knoll) that was started from the age of Paleocene to Miocene. In this study, the integration of seismic and well log data set is carried out to determine the chalk sand distribution in the Danish North Sea field. The integration of seismic and well log data set is performed by using the seismic inversion analysis and seismic multi-attribute. The seismic inversion algorithm, which is used to derive acoustic impedance (AI), is model-based technique. The derived AI is then used as external attributes for the input of multi-attribute analysis. Moreover, the multi-attribute analysis is used to generate the linear and non-linear transformation of among well log properties. In the case of the linear model, selected transformation is conducted by weighting step-wise linear regression (SWR), while for the non-linear model is performed by using probabilistic neural networks (PNN). The estimated porosity, which is resulted by PNN shows better suited to the well log data compared with the results of SWR. This result can be understood since PNN perform non-linear regression so that the relationship between the attribute data and predicted log data can be optimized. The distribution of chalk sand has been successfully identified and characterized by porosity value ranging from 23% up to 30%.

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

Bayesian outcome-based strategy classification.

PubMed

Lee, Michael D

2016-03-01

Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014) recently developed a method for making inferences about the decision processes people use in multi-attribute forced choice tasks. Their paper makes a number of worthwhile theoretical and methodological contributions. Theoretically, they provide an insightful psychological motivation for a probabilistic extension of the widely-used "weighted additive" (WADD) model, and show how this model, as well as other important models like "take-the-best" (TTB), can and should be expressed in terms of meaningful priors. Methodologically, they develop an inference approach based on the Minimum Description Length (MDL) principles that balances both the goodness-of-fit and complexity of the decision models they consider. This paper aims to preserve these useful contributions, but provide a complementary Bayesian approach with some theoretical and methodological advantages. We develop a simple graphical model, implemented in JAGS, that allows for fully Bayesian inferences about which models people use to make decisions. To demonstrate the Bayesian approach, we apply it to the models and data considered by Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014), showing how a prior predictive analysis of the models, and posterior inferences about which models people use and the parameter settings at which they use them, can contribute to our understanding of human decision making.

Preferences of colorectal cancer patients for treatment and decision-making: a systematic literature review.

PubMed

Damm, K; Vogel, A; Prenzler, A

2014-11-01

Treatment decisions in life-threatening diseases, like colorectal cancer (CRC), are crucial, since they have a great impact on patient's survival and health-related quality of life. Thereby, the inclusion of patient's preferences becomes more and more important; however, these first need to be identified. Therefore, we conducted a systematic literature review in 12 electronic databases, published between 2000 and 2012, in order to identify patient's preferences concerning treatment preferences and involvement in the decision-making process. Nineteen studies were included and thoroughly analysed. This review shows that CRC patients do have preferences regarding different treatment options and outcomes; however, these preferences are not homogenous and seem to depend on personal factors like age and gender. Despite the existence of these preferences, the majority of patients prefer a passive role in the decision-making process, which in part may be explained by the severity of the disease. Again, subgroup analyses reveal the impact of personal factors like gender and education on the preference. Due to the importance of personal factors in the analysis of patient preferences, we identified an urgent need for larger studies that are suitable for subgroup analyses and incorporate multi-attributive measurement techniques, like discrete choice methods. © 2014 John Wiley & Sons Ltd.

Embedding Human Expert Cognition Into Autonomous UAS Trajectory Planning.

PubMed

Narayan, Pritesh; Meyer, Patrick; Campbell, Duncan

2013-04-01

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

NASA Astrophysics Data System (ADS)

Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

2016-03-01

A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

Economics of human performance and systems total ownership cost.

PubMed

Onkham, Wilawan; Karwowski, Waldemar; Ahram, Tareq Z

2012-01-01

Financial costs of investing in people is associated with training, acquisition, recruiting, and resolving human errors have a significant impact on increased total ownership costs. These costs can also affect the exaggerate budgets and delayed schedules. The study of human performance economical assessment in the system acquisition process enhances the visibility of hidden cost drivers which support program management informed decisions. This paper presents the literature review of human total ownership cost (HTOC) and cost impacts on overall system performance. Economic value assessment models such as cost benefit analysis, risk-cost tradeoff analysis, expected value of utility function analysis (EV), growth readiness matrix, multi-attribute utility technique, and multi-regressions model were introduced to reflect the HTOC and human performance-technology tradeoffs in terms of the dollar value. The human total ownership regression model introduces to address the influencing human performance cost component measurement. Results from this study will increase understanding of relevant cost drivers in the system acquisition process over the long term.

Priority Determination of Underwater Tourism Site Development in Gorontalo Province using Analytical Hierarchy Process (AHP)

NASA Astrophysics Data System (ADS)

Rohandi, M.; Tuloli, M. Y.; Jassin, R. T.

2018-02-01

This research aims to determine the development of priority of underwater tourism in Gorontalo province using the Analytical Hierarchy Process (AHP) method which is one of DSS methods applying Multi-Attribute Decision Making (MADM). This method used 5 criteria and 28 alternatives to determine the best priority of underwater tourism site development in Gorontalo province. Based on the AHP calculation it appeared that the best priority development of underwater tourism site is Pulau Cinta whose total AHP score is 0.489 or 48.9%. This DSS produced a reliable result, faster solution, time-saving, and low cost for the decision makers to obtain the best underwater tourism site to be developed.

District Heating Systems Performance Analyses. Heat Energy Tariff

NASA Astrophysics Data System (ADS)

Ziemele, Jelena; Vigants, Girts; Vitolins, Valdis; Blumberga, Dagnija; Veidenbergs, Ivars

2014-12-01

The paper addresses an important element of the European energy sector: the evaluation of district heating (DH) system operations from the standpoint of increasing energy efficiency and increasing the use of renewable energy resources. This has been done by developing a new methodology for the evaluation of the heat tariff. The paper presents an algorithm of this methodology, which includes not only a data base and calculation equation systems, but also an integrated multi-criteria analysis module using MADM/MCDM (Multi-Attribute Decision Making / Multi-Criteria Decision Making) based on TOPSIS (Technique for Order Performance by Similarity to Ideal Solution). The results of the multi-criteria analysis are used to set the tariff benchmarks. The evaluation methodology has been tested for Latvian heat tariffs, and the obtained results show that only half of heating companies reach a benchmark value equal to 0.5 for the efficiency closeness to the ideal solution indicator. This means that the proposed evaluation methodology would not only allow companies to determine how they perform with regard to the proposed benchmark, but also to identify their need to restructure so that they may reach the level of a low-carbon business.

The Elasticity of Preferences.

PubMed

Simon, Dan; Spiller, Stephen A

2016-12-01

We explore how preferences for attributes are constructed when people choose between multiattribute options. As found in prior research, we observed that while people make decisions, their preferences for the attributes in question shift to support the emerging choice, thus enabling confident decisions. The novelty of the studies reported here is that participants repeated the same task 6 to 8 weeks later. We found that between tasks, preferences returned to near their original levels, only to shift again to support the second choice, regardless of which choice participants made. Similar patterns were observed in a free-choice task (Study 1) and when the favorableness of options was manipulated (Study 2). It follows that preferences behave in an elastic manner: In the absence of situational pressures, they rest at baseline levels, but during the process of reaching a decision, they morph to support the chosen options. This elasticity appears to facilitate confident decision making in the face of decisional conflict.

An interval-valued 2-tuple linguistic group decision-making model based on the Choquet integral operator

NASA Astrophysics Data System (ADS)

Liu, Bingsheng; Fu, Meiqing; Zhang, Shuibo; Xue, Bin; Zhou, Qi; Zhang, Shiruo

2018-01-01

The Choquet integral (IL) operator is an effective approach for handling interdependence among decision attributes in complex decision-making problems. However, the fuzzy measures of attributes and attribute sets required by IL are difficult to achieve directly, which limits the application of IL. This paper proposes a new method for determining fuzzy measures of attributes by extending Marichal's concept of entropy for fuzzy measure. To well represent the assessment information, interval-valued 2-tuple linguistic context is utilised to represent information. Then, we propose a Choquet integral operator in an interval-valued 2-tuple linguistic environment, which can effectively handle the correlation between attributes. In addition, we apply these methods to solve multi-attribute group decision-making problems. The feasibility and validity of the proposed operator is demonstrated by comparisons with other models in illustrative example part.

Intelligent data management for real-time spacecraft monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

1992-01-01

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

Analysis of student attitudes towards e-learning using Fishbein Multiattribute approach

NASA Astrophysics Data System (ADS)

Jasuli

2018-01-01

This research aimed to know students’ attitudes toward e-learning and to determine what attributes were considered to be dominant by students toward the use of e-learning. The research population was all postgraduate students in the 2016 academic year at Universitas Negeri Surabaya. The sampling technique is using nonprobability sampling and purposive sampling with the sample totaled 100 respondents. The research instrument is using questionnaire with semantic differential scale. The models used to analyze is multi-attribute Fishbein model. The findings indicated that student attitudes toward e-learning are positive and easy accessibility which is considered as the most important attribute by students toward the use of e-learning.

Benefits and risks of emerging technologies: integrating life cycle assessment and decision analysis to assess lumber treatment alternatives.

PubMed

Tsang, Michael P; Bates, Matthew E; Madison, Marcus; Linkov, Igor

2014-10-07

Assessing the best options among emerging technologies (e.g., new chemicals, nanotechnologies) is complicated because of trade-offs across benefits and risks that are difficult to quantify given limited and fragmented availability of information. This study demonstrates the integration of multicriteria decision analysis (MCDA) and life cycle assessment (LCA) to address technology alternative selection decisions. As a case study, prioritization of six lumber treatment alternatives [micronized copper quaternary (MCQ); alkaline copper quaternary (ACQ); water-borne copper naphthenate (CN); oil-borne copper naphthenate (CNo); water-borne copper quinolate (CQ); and water-borne zinc naphthenate (ZN)] for military use are considered. Multiattribute value theory (MAVT) is used to derive risk and benefit scores. Risk scores are calculated using a cradle-to-gate LCA. Benefit scores are calculated by scoring of cost, durability, and corrosiveness criteria. Three weighting schemes are used, representing Environmental, Military and Balanced stakeholder perspectives. Aggregated scores from all three perspectives show CQ to be the least favorable alterative. MCQ is identified as the most favorable alternative from the Environmental stakeholder perspective. From the Military stakeholder perspective, ZN is determined to be the most favorable alternative, followed closely by MCQ. This type of scoring and ranking of multiple heterogeneous criteria in a systematic and transparent way facilitates better justification of technology selection and regulation.

The Local Geometry of Multiattribute Tradeoff Preferences

PubMed Central

McGeachie, Michael; Doyle, Jon

2011-01-01

Existing representations for multiattribute ceteris paribus preference statements have provided useful treatments and clear semantics for qualitative comparisons, but have not provided similarly clear representations or semantics for comparisons involving quantitative tradeoffs. We use directional derivatives and other concepts from elementary differential geometry to interpret conditional multiattribute ceteris paribus preference comparisons that state bounds on quantitative tradeoff ratios. This semantics extends the familiar economic notion of marginal rate of substitution to multiple continuous or discrete attributes. The same geometric concepts also provide means for interpreting statements about the relative importance of different attributes. PMID:21528018

Structuring Process Evaluation to Forecast Use and Sustainability of an Intervention: Theory and Data From the Efficacy Trial for Lunch Is in the Bag.

PubMed

Roberts-Gray, Cindy; Sweitzer, Sara J; Ranjit, Nalini; Potratz, Christa; Rood, Magdalena; Romo-Palafox, Maria Jose; Byrd-Williams, Courtney E; Briley, Margaret E; Hoelscher, Deanna M

2017-08-01

A cluster-randomized trial at 30 early care and education centers (Intervention = 15, waitlist Control = 15) showed the Lunch Is in the Bag intervention increased parents' packing of fruits, vegetables, and whole grains in their preschool children's bag lunches (parent-child dyads = 351 Intervention, 282 Control). To examine the utility of structuring the trial's process evaluation to forecast use, sustainability, and readiness of the intervention for wider dissemination and implementation. Pretrial, the research team simulated user experience to forecast use of the intervention. Multiattribute evaluation of user experience measured during the trial assessed use and sustainability of the intervention. Thematic analysis of posttrial interviews with users evaluated sustained use and readiness for wider dissemination. Moderate use was forecast by the research team. Multiattribute evaluation of activity logs, surveys, and observations during the trial indicated use consistent with the forecast except that prevalence of parents reading the newsletters was greater (83% vs. 50%) and hearing their children talk about the classroom was less (4% vs. 50%) than forecast. Early care and education center-level likelihood of sustained use was projected to be near zero. Posttrial interviews indicated use was sustained at zero centers. Structuring the efficacy trial's process evaluation as a progression of assessments of user experience produced generally accurate forecasts of use and sustainability of the intervention at the trial sites. This approach can assist interpretation of trial outcomes, aid decisions about dissemination of the intervention, and contribute to translational science for improving health.

Salience driven value integration explains decision biases and preference reversal

PubMed Central

Tsetsos, Konstantinos; Chater, Nick; Usher, Marius

2012-01-01

Human choice behavior exhibits many paradoxical and challenging patterns. Traditional explanations focus on how values are represented, but little is known about how values are integrated. Here we outline a psychophysical task for value integration that can be used as a window on high-level, multiattribute decisions. Participants choose between alternative rapidly presented streams of numerical values. By controlling the temporal distribution of the values, we demonstrate that this process underlies many puzzling choice paradoxes, such as temporal, risk, and framing biases, as well as preference reversals. These phenomena can be explained by a simple mechanism based on the integration of values, weighted by their salience. The salience of a sampled value depends on its temporal order and momentary rank in the decision context, whereas the direction of the weighting is determined by the task framing. We show that many known choice anomalies may arise from the microstructure of the value integration process. PMID:22635271

[Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods].

PubMed

Qu, Cheng; Tang, Yu-Ping; Shi, Xu-Qin; Zhou, Gui-Sheng; Shang, Er-Xin; Shang, Li-Li; Guo, Jian-Ming; Liu, Pei; Zhao, Jing; Zhao, Bu-Chang; Duan, Jin-Ao

2017-08-01

To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibrinogen(FIB) were tested to observe the effects of DH herb pair with different preparations on blood coagulation function and platelet aggregation of blood stasis rats. Then PCA, hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods were all used to comprehensively evaluate the total promoting blood circulation and removing blood stasis effects of DH herb pair with different preparations. The hemorheological indexes and coagulation parameters of model group had significant differences with normal blank group. As compared with the model group, the DH herb pair with different preparations at low, middle and high doses could improve the blood hemorheology indexes and coagulation parameters in acute blood stasis rats with dose-effect relation. Based on the PCA, hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods, the high dose group of 50% alcohol extract had the best effect of promoting blood circulation and removing blood stasis. Under the same dose but different preparations, 50% alcohol DH could obviously improve the hemorheology and blood coagulation function in acute blood stasis rats. These results suggested that DH herb pair with different preparations could obviously ameliorate the abnormality of hemorheology and blood coagulation function in acute blood stasis rats, and the optimized preparation of DH herb pair on promoting blood effects was 50% alcohol extract, providing scientific basis for more effective application of the DH herb pair in modern clinic medicine. Copyright© by the Chinese Pharmaceutical Association.

Temporary site selection and decision-making methods: a case study of Tehran, Iran.

PubMed

Omidvar, Babak; Baradaran-Shoraka, Mohammad; Nojavan, Mehdi

2013-07-01

Decisions on selecting an appropriate site for temporary shelter used to be taken in a limited amount of time after a disaster. The need for a systematic method in this area inspired the MADM (multi-attribute decision making) for complex disaster management decisions. This research proposes a model for appropriate and systematic site selection for temporary shelters, before an earthquake, using a geographical information system and MADM based on an earthquake damage assessment. After the effective criteria for site selection of temporary shelters are determined, the geographical layers of these criteria are prepared for Municipal District No.1 of Greater Tehran, the capital of Iran. Given these attributes and the required shelter area (415-610 hectares), 14 zones are proposed initially. Various MADM methods are used for the final selection. The mean of the aggregated ranking results are determined, and 10 of the 14 initial zones are ranked. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.

Time Sharing Between Robotics and Process Control: Validating a Model of Attention Switching.

PubMed

Wickens, Christopher Dow; Gutzwiller, Robert S; Vieane, Alex; Clegg, Benjamin A; Sebok, Angelia; Janes, Jess

2016-03-01

The aim of this study was to validate the strategic task overload management (STOM) model that predicts task switching when concurrence is impossible. The STOM model predicts that in overload, tasks will be switched to, to the extent that they are attractive on task attributes of high priority, interest, and salience and low difficulty. But more-difficult tasks are less likely to be switched away from once they are being performed. In Experiment 1, participants performed four tasks of the Multi-Attribute Task Battery and provided task-switching data to inform the role of difficulty and priority. In Experiment 2, participants concurrently performed an environmental control task and a robotic arm simulation. Workload was varied by automation of arm movement and both the phases of environmental control and existence of decision support for fault management. Attention to the two tasks was measured using a head tracker. Experiment 1 revealed the lack of influence of task priority and confirmed the differing roles of task difficulty. In Experiment 2, the percentage attention allocation across the eight conditions was predicted by the STOM model when participants rated the four attributes. Model predictions were compared against empirical data and accounted for over 95% of variance in task allocation. More-difficult tasks were performed longer than easier tasks. Task priority does not influence allocation. The multiattribute decision model provided a good fit to the data. The STOM model is useful for predicting cognitive tunneling given that human-in-the-loop simulation is time-consuming and expensive. © 2016, Human Factors and Ergonomics Society.

Watermark: An Application and Methodology and Application for Interactive and intelligent Decision Support for Groundwater Systems

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.

2016-12-01

Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.

Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis.

PubMed

Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta

2017-01-01

In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants' choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection.

Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis

PubMed Central

Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta

2017-01-01

In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants’ choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection. PMID:28867996

Informing vaccine decision-making: A strategic multi-attribute ranking tool for vaccines-SMART Vaccines 2.0.

PubMed

Knobler, Stacey; Bok, Karin; Gellin, Bruce

2017-01-20

SMART Vaccines 2.0 software is being developed to support decision-making among multiple stakeholders in the process of prioritizing investments to optimize the outcomes of vaccine development and deployment. Vaccines and associated vaccination programs are one of the most successful and effective public health interventions to prevent communicable diseases and vaccine researchers are continually working towards expanding targets for communicable and non-communicable diseases through preventive and therapeutic modes. A growing body of evidence on emerging vaccine technologies, trends in disease burden, costs associated with vaccine development and deployment, and benefits derived from disease prevention through vaccination and a range of other factors can inform decision-making and investment in new and improved vaccines and targeted utilization of already existing vaccines. Recognizing that an array of inputs influences these decisions, the strategic multi-attribute ranking method for vaccines (SMART Vaccines 2.0) is in development as a web-based tool-modified from a U.S. Institute of Medicine Committee effort (IOM, 2015)-to highlight data needs and create transparency to facilitate dialogue and information-sharing among decision-makers and to optimize the investment of resources leading to improved health outcomes. Current development efforts of the SMART Vaccines 2.0 framework seek to generate a weighted recommendation on vaccine development or vaccination priorities based on population, disease, economic, and vaccine-specific data in combination with individual preference and weights of user-selected attributes incorporating valuations of health, economics, demographics, public concern, scientific and business, programmatic, and political considerations. Further development of the design and utility of the tool is being carried out by the National Vaccine Program Office of the Department of Health and Human Services and the Fogarty International Center of the National Institutes of Health. We aim to demonstrate the utility of SMART Vaccines 2.0 through the engagement of a community of relevant stakeholders and to identify a limited number of pilot projects to determine explicitly defined attribute preferences and the related data and model requirements that are responsive to user needs and able to improve the use of evidence for vaccine-related decision-making and consequential priorities of vaccination options. Copyright © 2016 Elsevier Ltd. All rights reserved.

Single-process versus multiple-strategy models of decision making: evidence from an information intrusion paradigm.

PubMed

Söllner, Anke; Bröder, Arndt; Glöckner, Andreas; Betsch, Tilmann

2014-02-01

When decision makers are confronted with different problems and situations, do they use a uniform mechanism as assumed by single-process models (SPMs) or do they choose adaptively from a set of available decision strategies as multiple-strategy models (MSMs) imply? Both frameworks of decision making have gathered a lot of support, but only rarely have they been contrasted with each other. Employing an information intrusion paradigm for multi-attribute decisions from givens, SPM and MSM predictions on information search, decision outcomes, attention, and confidence judgments were derived and tested against each other in two experiments. The results consistently support the SPM view: Participants seemingly using a "take-the-best" (TTB) strategy do not ignore TTB-irrelevant information as MSMs would predict, but adapt the amount of information searched, choose alternative choice options, and show varying confidence judgments contingent on the quality of the "irrelevant" information. The uniformity of these findings underlines the adequacy of the novel information intrusion paradigm and comprehensively promotes the notion of a uniform decision making mechanism as assumed by single-process models. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Multi-Attribute Sequential Search

ERIC Educational Resources Information Center

Bearden, J. Neil; Connolly, Terry

2007-01-01

This article describes empirical and theoretical results from two multi-attribute sequential search tasks. In both tasks, the DM sequentially encounters options described by two attributes and must pay to learn the values of the attributes. In the "continuous" version of the task the DM learns the precise numerical value of an attribute when she…

The Valuation of Scientific and Technical Experiments

NASA Technical Reports Server (NTRS)

Williams, F. E.

1972-01-01

Rational selection of scientific and technical experiments for space missions is studied. Particular emphasis is placed on the assessment of value or worth of an experiment. A specification procedure is outlined and discussed for the case of one decision maker. Experiments are viewed as multi-attributed entities, and a relevant set of attributes is proposed. Alternative methods of describing levels of the attributes are proposed and discussed. The reasonableness of certain simplifying assumptions such as preferential and utility independence is explored, and it is tentatively concluded that preferential independence applies and utility independence appears to be appropriate.

EXPERIMENTING WITH MULTI-ATTRIBUTE UTILITY SURVEY METHODS IN A MULTI-DIMENSIONAL VALUATION PROBLEM. (R824699)

EPA Science Inventory

Abstract

The use of willingness-to-pay (WTP) survey techniques based on multi-attribute utility (MAU) approaches has been recommended by some authors as a way to deal simultaneously with two difficulties that increasingly plague environmental valuation. The first of th...

Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning

PubMed Central

Maurer, Max; Lienert, Judit

2017-01-01

We compare the use of multi-criteria decision analysis (MCDA)–or more precisely, models used in multi-attribute value theory (MAVT)–to integrated assessment (IA) models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability), desirability (value), and distinguishability (value range) of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water supply planning in the case study and beyond. PMID:28481881

Assessment of Trading Partners for China's Rare Earth Exports Using a Decision Analytic Approach

PubMed Central

He, Chunyan; Lei, Yalin; Ge, Jianping

2014-01-01

Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies. PMID:25051534

Assessment of trading partners for China's rare earth exports using a decision analytic approach.

PubMed

He, Chunyan; Lei, Yalin; Ge, Jianping

2014-01-01

Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies.

Evaluation of the Parent-Implemented Communication Strategies (PiCS) Project Using the Multiattribute Utility (MAU) Approach

ERIC Educational Resources Information Center

Stoner, Julia B.; Meadan, Hedda; Angell, Maureen E.; Daczewitz, Marcus

2012-01-01

We conducted a multiattribute utility (MAU) evaluation to assess the Parent-Implemented Communication Strategies (PiCS) project which was funded by the Institute of Education Sciences (IES). In the PiCS project parents of young children with developmental disabilities are trained and coached in their homes on naturalistic and visual teaching…

Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

NASA Astrophysics Data System (ADS)

Majumder, Himadri; Maity, Kalipada

2018-03-01

Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

A decision support for an integrated multi-scale analysis of irrigation: DSIRR.

PubMed

Bazzani, Guido M

2005-12-01

The paper presents a decision support designed to conduct an economic-environmental assessment of the agricultural activity focusing on irrigation called 'Decision Support for IRRigated Agriculture' (DSIRR). The program describes the effect at catchment scale of choices taken at micro scale by independent actors, the farmers, by simulating their decision process. The decision support (DS) has been thought of as a support tool for participatory water policies as requested by the Water Framework Directive and it aims at analyzing alternatives in production and technology, according to different market, policy and climate conditions. The tool uses data and models, provides a graphical user interface and can incorporate the decision makers' own insights. Heterogeneity in preferences is admitted since it is assumed that irrigators try to optimize personal multi-attribute utility functions, subject to a set of constraints. Consideration of agronomic and engineering aspects allows an accurate description of irrigation. Mathematical programming techniques are applied to find solutions. The program has been applied in the river Po basin (northern Italy) to analyze the impact of a pricing policy in a context of irrigation technology innovation. Water demand functions and elasticity to water price have been estimated. Results demonstrate how different areas and systems react to the same policy in quite a different way. While in the annual cropping system pricing seems effective to save the resource at the cost of impeding Water Agencies cost recovery, the same policy has an opposite effect in the perennial fruit system which shows an inelastic response to water price. The multidimensional assessment conducted clarified the trades-off among conflicting economic-social-environmental objectives, thus generating valuable information to design a more tailored mix of measures.

The conceptual foundation of environmental decision support.

PubMed

Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

2015-05-01

Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A response-time approach to comparing generalized rational and take-the-best models of decision making.

PubMed

Bergert, F Bryan; Nosofsky, Robert M

2007-01-01

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT) approach. TTB predicts that RT is determined solely by the expected time required to locate the 1st discriminating attribute, whereas RAT predicts that RT is determined by the difference in summed evidence between the 2 alternatives. Critical test pairs are used that partially decouple these 2 factors. Under conditions in which ideal observer TTB and RAT strategies yield equivalent decisions, both the RT results and the estimated attribute weights suggest that the vast majority of subjects adopted the generalized TTB strategy. The RT approach is also validated in an experimental condition in which use of a RAT strategy is essentially forced upon subjects. (c) 2007 APA, all rights reserved.

Rough Evaluation Structure: Application of Rough Set Theory to Generate Simple Rules for Inconsistent Preference Relation

NASA Astrophysics Data System (ADS)

Gehrmann, Andreas; Nagai, Yoshimitsu; Yoshida, Osamu; Ishizu, Syohei

Since management decision-making becomes complex and preferences of the decision-maker frequently becomes inconsistent, multi-attribute decision-making problems were studied. To represent inconsistent preference relation, the concept of evaluation structure was introduced. We can generate simple rules to represent inconsistent preference relation by the evaluation structures. Further rough set theory for the preference relation was studied and the concept of approximation was introduced. One of our main aims of this paper is to introduce a concept of rough evaluation structure for representing inconsistent preference relation. We apply rough set theory to the evaluation structure, and develop a method for generating simple rules for inconsistent preference relations. In this paper, we introduce concepts of totally ordered information system, similarity class of preference relation, upper and lower approximation of preference relations. We also show the properties of rough evaluation structure and provide a simple example. As an application of rough evaluation structure, we analyze questionnaire survey of customer preferences about audio players.

Maclaurin symmetric mean operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decision-making

NASA Astrophysics Data System (ADS)

Liu, Peide; Qin, Xiyou

2017-11-01

Linguistic intuitionistic fuzzy number (LIFN) is a special intuitionistic fuzzy number which can more easily describe the vagueness existing in the real decision-making. Maclaurin symmetric mean (MSM) operator has the characteristic of considering the interrelationships among any number of input parameters. In this paper, we extended the MSM operator to the LIFNs and some extended MSM operators for LIFNs were proposed, some new decision-making methods were developed. Firstly, we introduced the definition, score function, properties and operational rules of the LIFNs. Then, we proposed some linguistic intuitionistic fuzzy MSM operators, such as linguistic intuitionistic fuzzy Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy Maclaurin symmetric mean (WLIFMSM) operator, linguistic intuitionistic fuzzy dual Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy dual Maclaurin symmetric mean (WLIFDMSM) operator. In the meantime, we studied some important properties of these operators, and developed some methods based on WLIFMSM operator and WLIFDMSM operator for multi-attribute decision-making. Finally, we use an example to demonstrate the effectiveness of the proposed methods.

Analysis of Generation Y Workforce Motivation Using Multiattribute Utility Theory

DTIC Science & Technology

2011-01-01

careers and professional development (Westerman and Yamamura, 2007; Kim et al., 2009; Zemke et al., 2000). Generation Y aspires for a work / life balance (Crumpacker...within the federal govern- ment. The majority of Generation Y research is done on the work / life balance factor. Research points to this new

Averaging Models: Parameters Estimation with the R-Average Procedure

ERIC Educational Resources Information Center

Vidotto, G.; Massidda, D.; Noventa, S.

2010-01-01

The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982), can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto &…

Deriving preference order of post-mining land-uses through MLSA framework: application of an outranking technique

NASA Astrophysics Data System (ADS)

Soltanmohammadi, Hossein; Osanloo, Morteza; Aghajani Bazzazi, Abbas

2009-08-01

This study intends to take advantage of a previously developed framework for mined land suitability analysis (MLSA) consisted of economical, social, technical and mine site factors to achieve a partial and also a complete pre-order of feasible post-mining land-uses. Analysis by an outranking multi-attribute decision-making (MADM) technique, called PROMETHEE (preference ranking organization method for enrichment evaluation), was taken into consideration because of its clear advantages on the field of MLSA as compared with MADM ranking techniques. Application of the proposed approach on a mined land can be completed through some successive steps. First, performance of the MLSA attributes is scored locally by each individual decision maker (DM). Then the assigned performance scores are normalized and the deviation amplitudes of non-dominated alternatives are calculated. Weights of the attributes are calculated by another MADM technique namely, analytical hierarchy process (AHP) in a separate procedure. Using the Gaussian preference function beside the weights, the preference indexes of the land-use alternatives are obtained. Calculation of the outgoing and entering flows of the alternatives and one by one comparison of these values will lead to partial pre-order of them and calculation of the net flows, will lead to a ranked preference for each land-use. At the final step, utilizing the PROMETHEE group decision support system which incorporates judgments of all the DMs, a consensual ranking can be derived. In this paper, preference order of post-mining land-uses for a hypothetical mined land has been derived according to judgments of one DM to reveal applicability of the proposed approach.

A Three Stage Multi-attribute Procurement Auction: A Proposal for Department of Defense (DoD) Vendor Selection Decisions.

DTIC Science & Technology

2010-04-30

regarding production capabilities and costs, but must somehow form beliefs about the likelihood of a bid being accepted. We facilitate formulation...which both vendors believe the buyer places equal weight on the two attributes, but the vendors differ in their capabilities of producing those...exchange—the future of B2B . Harvard Business Review, 78(6), 86-96. = ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= do^ar^qb=p`elli=lc=_rpfkbpp=C=mr_if`=mlif`v= 444= k^s^i

A visual analysis of multi-attribute data using pixel matrix displays

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel; Schreck, Tobias

2007-01-01

Charts and tables are commonly used to visually analyze data. These graphics are simple and easy to understand, but charts show only highly aggregated data and present only a limited number of data values while tables often show too many data values. As a consequence, these graphics may either lose or obscure important information, so different techniques are required to monitor complex datasets. Users need more powerful visualization techniques to digest and compare detailed multi-attribute data to analyze the health of their business. This paper proposes an innovative solution based on the use of pixel-matrix displays to represent transaction-level information. With pixelmatrices, users can visualize areas of importance at a glance, a capability not provided by common charting techniques. We present our solutions to use colored pixel-matrices in (1) charts for visualizing data patterns and discovering exceptions, (2) tables for visualizing correlations and finding root-causes, and (3) time series for visualizing the evolution of long-running transactions. The solutions have been applied with success to product sales, Internet network performance analysis, and service contract applications demonstrating the benefits of our method over conventional graphics. The method is especially useful when detailed information is a key part of the analysis.

A new multicriteria risk mapping approach based on a multiattribute frontier concept

Treesearch

Denys Yemshanov; Frank H. Koch; Yakov Ben-Haim; Marla Downing; Frank Sapio; Marty Siltanen

2013-01-01

Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that...

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education

PubMed Central

PHELPS, CHARLES; RAPPUOLI, RINO; LEVIN, SCOTT; SHORTLIFFE, EDWARD; COLWELL, RITA

2016-01-01

Policy Points: Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning.Public health agencies’ current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost‐effectiveness.As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost‐effectiveness analyses widely recommended and used for public health planning.Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Context Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost‐effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Methods Our work employed a multicriteria systems analysis approach—specifically, multiattribute utility theory—to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost‐effectiveness analysis approach. Findings (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost‐effectiveness analysis. (2) More sophisticated systems‐level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. Conclusions The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost‐effectiveness analysis. The Strategic Multi‐Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. PMID:26994711

Expanding the Reach of Participatory Risk Management: Testing an Online Decision-Aiding Framework for Informing Internally Consistent Choices.

PubMed

Bessette, Douglas L; Campbell-Arvai, Victoria; Arvai, Joseph

2016-05-01

This article presents research aimed at developing and testing an online, multistakeholder decision-aiding framework for informing multiattribute risk management choices associated with energy development and climate change. The framework was designed to provide necessary background information and facilitate internally consistent choices, or choices that are in line with users' prioritized objectives. In order to test different components of the decision-aiding framework, a six-part, 2 × 2 × 2 factorial experiment was conducted, yielding eight treatment scenarios. The three factors included: (1) whether or not users could construct their own alternatives; (2) the level of detail regarding the composition of alternatives users would evaluate; and (3) the way in which a final choice between users' own constructed (or highest-ranked) portfolio and an internally consistent portfolio was presented. Participants' self-reports revealed the framework was easy to use and providing an opportunity to develop one's own risk-management alternatives (Factor 1) led to the highest knowledge gains. Empirical measures showed the internal consistency of users' decisions across all treatments to be lower than expected and confirmed that providing information about alternatives' composition (Factor 2) resulted in the least internally consistent choices. At the same time, those users who did not develop their own alternatives and were not shown detailed information about the composition of alternatives believed their choices to be the most internally consistent. These results raise concerns about how the amount of information provided and the ability to construct alternatives may inversely affect users' real and perceived internal consistency. © 2015 Society for Risk Analysis.

A decision support tool to prioritize risk management options for contaminated sites.

PubMed

Sorvari, Jaana; Seppälä, Jyri

2010-03-15

The decisions on risk management (RM) of contaminated sites in Finland have typically been driven by practical factors such as time and money. However, RM is a multifaceted task that generally involves several additional determinants, e.g. performance and environmental effects of remediation methods, psychological and social factors. Therefore, we adopted a multi-criteria decision analysis approach and developed a decision support tool (DST) that is viable in decision-making in such a complex situation. The basic components of the DST are based on the Dutch REC system. However, our DST is more case-specific and allows the consideration of the type, magnitude and scale of contamination, land use, environmental conditions and socio-cultural aspects (e.g. loss of cultural heritage, image aspects). The construction of the DST was started by structuring the decision problem using a value tree. Based on this work we adopted the Multi-Attribute Value Theory (MAVT) for data aggregation. The final DST was demonstrated by two model sites for which the RM alternatives and site-specific data were created on the basis of factual remediation projects and by interviewing experts. The demonstration of the DST was carried out in a workshop where representatives of different stakeholders were requested to rank and weight the decision criteria involved. To get information on the consistency of the ranking of the RM alternatives, we used different weighting techniques (ratio estimation and pair-wise weighting) and alternative ways to treat individual respondents' weights in calculating the preference scores for each RM alternative. These dissimilar approaches resulted in some differences in the preference order of the RM alternatives. The demonstration showed that attention has to be paid to the proper description of the site, the principles of the procedure and the decision criteria. Nevertheless, the procedure proved to enable efficient communication between different stakeholders and the identification of the preferred RM option.

An Updated Version of the U.S. Air Force Multi-Attribute Task Battery (AF-MATB)

DTIC Science & Technology

2014-08-01

assessing human performance in a controlled multitask environment. The most recent release of AF-MATB contains numerous improvements and additions...Strategic Behavior, MATB, Multitasking , Task Battery, Simulator, Multi-Attribute Task Battery, Automation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...performance and multitasking strategy. As a result, a specific Information Throughput (IT) Mode was designed to customize the task to fit the Human

A Quadrupole Dalton-based multi-attribute method for product characterization, process development, and quality control of therapeutic proteins.

PubMed

Xu, Weichen; Jimenez, Rod Brian; Mowery, Rachel; Luo, Haibin; Cao, Mingyan; Agarwal, Nitin; Ramos, Irina; Wang, Xiangyang; Wang, Jihong

2017-10-01

During manufacturing and storage process, therapeutic proteins are subject to various post-translational modifications (PTMs), such as isomerization, deamidation, oxidation, disulfide bond modifications and glycosylation. Certain PTMs may affect bioactivity, stability or pharmacokinetics and pharmacodynamics profile and are therefore classified as potential critical quality attributes (pCQAs). Identifying, monitoring and controlling these PTMs are usually key elements of the Quality by Design (QbD) approach. Traditionally, multiple analytical methods are utilized for these purposes, which is time consuming and costly. In recent years, multi-attribute monitoring methods have been developed in the biopharmaceutical industry. However, these methods combine high-end mass spectrometry with complicated data analysis software, which could pose difficulty when implementing in a quality control (QC) environment. Here we report a multi-attribute method (MAM) using a Quadrupole Dalton (QDa) mass detector to selectively monitor and quantitate PTMs in a therapeutic monoclonal antibody. The result output from the QDa-based MAM is straightforward and automatic. Evaluation results indicate this method provides comparable results to the traditional assays. To ensure future application in the QC environment, this method was qualified according to the International Conference on Harmonization (ICH) guideline and applied in the characterization of drug substance and stability samples. The QDa-based MAM is shown to be an extremely useful tool for product and process characterization studies that facilitates facile understanding of process impact on multiple quality attributes, while being QC friendly and cost-effective.

Comparing capacity coefficient and dual task assessment of visual multitasking workload

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blaha, Leslie M.

Capacity coefficient analysis could offer a theoretically grounded alternative approach to subjective measures and dual task assessment of cognitive workload. Workload capacity or workload efficiency is a human information processing modeling construct defined as the amount of information that can be processed by the visual cognitive system given a specified of amount of time. In this paper, I explore the relationship between capacity coefficient analysis of workload efficiency and dual task response time measures. To capture multitasking performance, I examine how the relatively simple assumptions underlying the capacity construct generalize beyond the single visual decision making tasks. The fundamental toolsmore » for measuring workload efficiency are the integrated hazard and reverse hazard functions of response times, which are defined by log transforms of the response time distribution. These functions are used in the capacity coefficient analysis to provide a functional assessment of the amount of work completed by the cognitive system over the entire range of response times. For the study of visual multitasking, capacity coefficient analysis enables a comparison of visual information throughput as the number of tasks increases from one to two to any number of simultaneous tasks. I illustrate the use of capacity coefficients for visual multitasking on sample data from dynamic multitasking in the modified Multi-attribute Task Battery.« less

Responding to Vaccine Safety Signals during Pandemic Influenza: A Modeling Study

PubMed Central

Maro, Judith C.; Fryback, Dennis G.; Lieu, Tracy A.; Lee, Grace M.; Martin, David B.

2014-01-01

Background Managing emerging vaccine safety signals during an influenza pandemic is challenging. Federal regulators must balance vaccine risks against benefits while maintaining public confidence in the public health system. Methods We developed a multi-criteria decision analysis model to explore regulatory decision-making in the context of emerging vaccine safety signals during a pandemic. We simulated vaccine safety surveillance system capabilities and used an age-structured compartmental model to develop potential pandemic scenarios. We used an expert-derived multi-attribute utility function to evaluate potential regulatory responses by combining four outcome measures into a single measure of interest: 1) expected vaccination benefit from averted influenza; 2) expected vaccination risk from vaccine-associated febrile seizures; 3) expected vaccination risk from vaccine-associated Guillain-Barre Syndrome; and 4) expected change in vaccine-seeking behavior in future influenza seasons. Results Over multiple scenarios, risk communication, with or without suspension of vaccination of high-risk persons, were the consistently preferred regulatory responses over no action or general suspension when safety signals were detected during a pandemic influenza. On average, the expert panel valued near-term vaccine-related outcomes relative to long-term projected outcomes by 3∶1. However, when decision-makers had minimal ability to influence near-term outcomes, the response was selected primarily by projected impacts on future vaccine-seeking behavior. Conclusions The selected regulatory response depends on how quickly a vaccine safety signal is identified relative to the peak of the pandemic and the initiation of vaccination. Our analysis suggested two areas for future investment: efforts to improve the size and timeliness of the surveillance system and behavioral research to understand changes in vaccine-seeking behavior. PMID:25536228

Relative saliency in change signals affects perceptual comparison and decision processes in change detection.

PubMed

Yang, Cheng-Ta

2011-12-01

Change detection requires perceptual comparison and decision processes on different features of multiattribute objects. How relative salience between two feature-changes influences the processes has not been addressed. This study used the systems factorial technology to investigate the processes when detecting changes in a Gabor patch with visual inputs from orientation and spatial frequency channels. Two feature-changes were equally salient in Experiment 1, but a frequency-change was more salient than an orientation-change in Experiment 2. Results showed that all four observers adopted parallel self-terminating processing with limited- to unlimited-capacity processing in Experiment 1. In Experiment 2, one observer used parallel self-terminating processing with unlimited-capacity processing, and the others adopted serial self-terminating processing with limited- to unlimited-capacity processing to detect changes. Postexperimental interview revealed that subjective utility of feature information underlay the adoption of a decision strategy. These results highlight that observers alter decision strategies in change detection depending on the relative saliency in change signals, with relative saliency being determined by both physical salience and subjective weight of feature information. When relative salience exists, individual differences in the process characteristics emerge.

Systems modeling and analysis for Saudi Arabian electric power requirements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Al-Mohawes, N.A.

This thesis addresses the long-range generation planning problem in Saudi Arabia up to the year 2000. The first part presents various models for electric energy consumption in the residential and industrial sectors. These models can be used by the decision makers for the purposes of policy analysis, evaluation, and forecasting. Forecasts of energy in each sector are obtained from two different models for each sector. These models are based on two forecasting techniques: (1) Hybrid econometric/time series model. The idea of adaptive smoothing was utilized to produce forecasts under several scenarios. (2) Box-Jenkins time series technique. Box-Jenkins models and forecastsmore » are developed for the monthly number of electric consumers and the monthly energy consumption per consumer. The results obtained indicate that high energy consumption is expected during the coming two decades which necessitate serious energy assessment and optimization. Optimization of a mix of energy sources was considered using the group multiattribute utility (MAU) function. The results of MAU for three classes of decision makers (managerial, technical, and consumers) are developed through personal interactions. The computer package WASP was also used to develop a tentative optimum plan. According to this plan, four heavy-water nuclear power plants (800 MW) and four light-water nuclear power plants (1200 MW) have to be introduced by the year 2000 in addition to sixteen oil-fired power plants (400 MW) and nine gas turbines (100 MW).« less

Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space

PubMed Central

McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon

2015-01-01

Introduction Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses—where outcomes are considered separately, with their joint relationship under uncertainty ignored—lead to incorrect inference regarding preferred strategies. Objective The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Methods Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Results Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Conclusion Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple effects under uncertainty across potential threshold values for effect, better informing net benefit assessment and related reimbursement and research decisions. PMID:25751629

Measurements of Rationality: Individual Differences in Information Processing, the Transitivity of Preferences and Decision Strategies

PubMed Central

Sleboda, Patrycja; Sokolowska, Joanna

2017-01-01

The first goal of this study was to validate the Rational-Experiential Inventory (REI) and the Cognitive Reflection Test (CRT) through checking their relation to the transitivity axiom. The second goal was to test the relation between decision strategies and cognitive style as well as the relation between decision strategies and the transitivity of preferences. The following characteristics of strategies were investigated: requirements for trade-offs, maximization vs. satisficing and option-wise vs. attribute-wise information processing. Respondents were given choices between two multi-attribute options. The options were designed so that the choice indicated which strategy was applied. Both the REI-R and the CRT were found to be good predictors of the transitivity of preferences. Respondents who applied compensatory strategies and the maximization criterion scored highly on the REI-R and in the CRT, whereas those who applied the satisficing rule scored highly on the REI-R but not in the CRT. Attribute-wise information processing was related to low scores in both measurements. Option-wise information processing led to a high transitivity of preferences. PMID:29093695

Measurements of Rationality: Individual Differences in Information Processing, the Transitivity of Preferences and Decision Strategies.

PubMed

Sleboda, Patrycja; Sokolowska, Joanna

2017-01-01

The first goal of this study was to validate the Rational-Experiential Inventory ( REI ) and the Cognitive Reflection Test ( CRT ) through checking their relation to the transitivity axiom. The second goal was to test the relation between decision strategies and cognitive style as well as the relation between decision strategies and the transitivity of preferences. The following characteristics of strategies were investigated: requirements for trade-offs, maximization vs. satisficing and option-wise vs. attribute-wise information processing. Respondents were given choices between two multi-attribute options. The options were designed so that the choice indicated which strategy was applied. Both the REI-R and the CRT were found to be good predictors of the transitivity of preferences. Respondents who applied compensatory strategies and the maximization criterion scored highly on the REI-R and in the CRT , whereas those who applied the satisficing rule scored highly on the REI-R but not in the CRT . Attribute-wise information processing was related to low scores in both measurements. Option-wise information processing led to a high transitivity of preferences.

Patients were more consistent in randomized trial at prioritizing childbirth preferences using graphic-numeric than verbal formats.

PubMed

Eden, Karen B; Dolan, James G; Perrin, Nancy A; Kocaoglu, Dundar; Anderson, Nicholas; Case, James; Guise, Jeanne-Marie

2009-04-01

We developed an evidence-based decision aid to help women with a prior cesarean to prioritize their childbirth preferences related to a future birth. Because there was uncertainty about which scale format would assist the patients in being most consistent in prioritizing preferences in a multiattribute decision model, we compared a graphic-numeric scale with a text-anchored scale. Ninety-six postnatal women with a prior cesarean were randomized to use 1 of 2 preference scale formats in a computerized childbirth decision aid. We measured the level of inconsistency (intransitivity) when patients prioritized their childbirth preferences and clarity of values before and after using the decision aid. When the trade-offs involved risk, women were more consistent when using graphic-numeric than text-anchored formats (P=0.015). They prioritized safety to their baby as 4 times more important than any other decision factor including safety to self. Both groups reduced unclear childbirth values over time (P<0.001). Women who over-used the extreme ends of the scale when evaluating risk were more likely to be inconsistent (P<0.001). Patients were more consistent in making trade-offs involving risk using graphic-numeric formats than text-anchored formats to measure patient preferences.

Qualitative and quantitative comparison of geostatistical techniques of porosity prediction from the seismic and logging data: a case study from the Blackfoot Field, Alberta, Canada

NASA Astrophysics Data System (ADS)

Maurya, S. P.; Singh, K. H.; Singh, N. P.

2018-05-01

In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model based inversion and colored inversion techniques. The principle objective of the study is to find the suitable combination of seismic inversion and geostatistical techniques to predict porosity and identification of prospective zones in 3D seismic volume. The porosity estimated from these geostatistical approaches is corroborated with the well log porosity. The results suggest that all the three implemented geostatistical methods are efficient and reliable to predict the porosity but the multi-attribute and probabilistic neural network analysis provide more accurate and high resolution porosity sections. A low impedance (6000-8000 m/s g/cc) and high porosity (> 15%) zone is interpreted from inverted impedance and porosity sections respectively between 1060 and 1075 ms time interval and is characterized as reservoir. The qualitative and quantitative results demonstrate that of all the employed geostatistical methods, the probabilistic neural network along with model based inversion is the most efficient method for predicting porosity in inter well region.

Contribution of the multi-attribute value theory to conflict resolution in groundwater management - application to the Mancha Oriental groundwater system, Spain

NASA Astrophysics Data System (ADS)

Apperl, B.; Pulido-Velazquez, M.; Andreu, J.; Karjalainen, T. P.

2015-03-01

The implementation of the EU Water Framework Directive demands participatory water resource management approaches. Decision making in groundwater quantity and quality management is complex because of the existence of many independent actors, heterogeneous stakeholder interests, multiple objectives, different potential policies, and uncertain outcomes. Conflicting stakeholder interests have often been identified as an impediment to the realisation and success of water regulations and policies. The management of complex groundwater systems requires the clarification of stakeholders' positions (identifying stakeholder preferences and values), improving transparency with respect to outcomes of alternatives, and moving the discussion from the selection of alternatives towards the definition of fundamental objectives (value-thinking approach), which facilitates negotiation. The aims of the study are to analyse the potential of the multi-attribute value theory for conflict resolution in groundwater management and to evaluate the benefit of stakeholder incorporation into the different stages of the planning process, to find an overall satisfying solution for groundwater management. The research was conducted in the Mancha Oriental groundwater system (Spain), subject to intensive use of groundwater for irrigation. A complex set of objectives and attributes was defined, and the management alternatives were created by a combination of different fundamental actions, considering different implementation stages and future changes in water resource availability. Interviews were conducted with representative stakeholder groups using an interactive platform, showing simultaneously the consequences of changes in preferences to the alternative ranking. Results show that the approval of alternatives depends strongly on the combination of measures and the implementation stages. Uncertainties in the results were notable, but did not influence the alternative ranking heavily. The expected reduction in future groundwater resources by climate change increases the conflict potential. The implementation of the method in a very complex case study, with many conflicting objectives and alternatives and uncertain outcomes, including future scenarios under water limiting conditions, illustrates the potential of the method for supporting management decisions.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

PubMed

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

Assessing Women's Preferences and Preference Modeling for Breast Reconstruction Decision-Making.

PubMed

Sun, Clement S; Cantor, Scott B; Reece, Gregory P; Crosby, Melissa A; Fingeret, Michelle C; Markey, Mia K

2014-03-01

Women considering breast reconstruction must make challenging trade-offs amongst issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using nine different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual wellbeing as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants' rankings. The median amount of time required to assess preferences was 34 minutes. Agreement among the nine preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best performing risk averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the seven attributes. We recommend the risk averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study.

Optimization of the decision-making process for the selection of therapeutics to undergo clinical testing for spinal cord injury in the North American Clinical Trials Network.

PubMed

Guest, James; Harrop, James S; Aarabi, Bizhan; Grossman, Robert G; Fawcett, James W; Fehlings, Michael G; Tator, Charles H

2012-09-01

The North American Clinical Trials Network (NACTN) includes 9 clinical centers funded by the US Department of Defense and the Christopher Reeve Paralysis Foundation. Its purpose is to accelerate clinical testing of promising therapeutics in spinal cord injury (SCI) through the development of a robust interactive infrastructure. This structure includes key committees that serve to provide longitudinal guidance to the Network. These committees include the Executive, Data Management, and Neurological Outcome Assessments Committees, and the Therapeutic Selection Committee (TSC), which is the subject of this manuscript. The NACTN brings unique elements to the SCI field. The Network's stability is not restricted to a single clinical trial. Network members have diverse expertise and include experts in clinical care, clinical trial design and methodology, pharmacology, preclinical and clinical research, and advanced rehabilitation techniques. Frequent systematic communication is assigned a high value, as is democratic process, fairness and efficiency of decision making, and resource allocation. This article focuses on how decision making occurs within the TSC to rank alternative therapeutics according to 2 main variables: quality of the preclinical data set, and fit with the Network's aims and capabilities. This selection process is important because if the Network's resources are committed to a therapeutic, alternatives cannot be pursued. A proposed methodology includes a multicriteria decision analysis that uses a Multi-Attribute Global Inference of Quality matrix to quantify the process. To rank therapeutics, the TSC uses a series of consensus steps designed to reduce individual and group bias and limit subjectivity. Given the difficulties encountered by industry in completing clinical trials in SCI, stable collaborative not-for-profit consortia, such as the NACTN, may be essential to clinical progress in SCI. The evolution of the NACTN also offers substantial opportunity to refine decision making and group dynamics. Making the best possible decisions concerning therapeutics selection for trial testing is a cornerstone of the Network's function.

Underground Mining Method Selection Using WPM and PROMETHEE

NASA Astrophysics Data System (ADS)

Balusa, Bhanu Chander; Singam, Jayanthu

2018-04-01

The aim of this paper is to represent the solution to the problem of selecting suitable underground mining method for the mining industry. It is achieved by using two multi-attribute decision making techniques. These two techniques are weighted product method (WPM) and preference ranking organization method for enrichment evaluation (PROMETHEE). In this paper, analytic hierarchy process is used for weight's calculation of the attributes (i.e. parameters which are used in this paper). Mining method selection depends on physical parameters, mechanical parameters, economical parameters and technical parameters. WPM and PROMETHEE techniques have the ability to consider the relationship between the parameters and mining methods. The proposed techniques give higher accuracy and faster computation capability when compared with other decision making techniques. The proposed techniques are presented to determine the effective mining method for bauxite mine. The results of these techniques are compared with methods used in the earlier research works. The results show, conventional cut and fill method is the most suitable mining method.

The effects of nutrition labeling on consumer food choice: a psychological experiment and computational model.

PubMed

Helfer, Peter; Shultz, Thomas R

2014-12-01

The widespread availability of calorie-dense food is believed to be a contributing cause of an epidemic of obesity and associated diseases throughout the world. One possible countermeasure is to empower consumers to make healthier food choices with useful nutrition labeling. An important part of this endeavor is to determine the usability of existing and proposed labeling schemes. Here, we report an experiment on how four different labeling schemes affect the speed and nutritional value of food choices. We then apply decision field theory, a leading computational model of human decision making, to simulate the experimental results. The psychology experiment shows that quantitative, single-attribute labeling schemes have greater usability than multiattribute and binary ones, and that they remain effective under moderate time pressure. The computational model simulates these psychological results and provides explanatory insights into them. This work shows how experimental psychology and computational modeling can contribute to the evaluation and improvement of nutrition-labeling schemes. © 2014 New York Academy of Sciences.

Visual Attention Allocation Between Robotic Arm and Environmental Process Control: Validating the STOM Task Switching Model

NASA Technical Reports Server (NTRS)

Wickens, Christopher; Vieanne, Alex; Clegg, Benjamin; Sebok, Angelia; Janes, Jessica

2015-01-01

Fifty six participants time shared a spacecraft environmental control system task with a realistic space robotic arm control task in either a manual or highly automated version. The former could suffer minor failures, whose diagnosis and repair were supported by a decision aid. At the end of the experiment this decision aid unexpectedly failed. We measured visual attention allocation and switching between the two tasks, in each of the eight conditions formed by manual-automated arm X expected-unexpected failure X monitoring- failure management. We also used our multi-attribute task switching model, based on task attributes of priority interest, difficulty and salience that were self-rated by participants, to predict allocation. An un-weighted model based on attributes of difficulty, interest and salience accounted for 96 percent of the task allocation variance across the 8 different conditions. Task difficulty served as an attractor, with more difficult tasks increasing the tendency to stay on task.

Some Muirhead Mean Operators for Intuitionistic Fuzzy Numbers and Their Applications to Group Decision Making.

PubMed

Liu, Peide; Li, Dengfeng

2017-01-01

Muirhead mean (MM) is a well-known aggregation operator which can consider interrelationships among any number of arguments assigned by a variable vector. Besides, it is a universal operator since it can contain other general operators by assigning some special parameter values. However, the MM can only process the crisp numbers. Inspired by the MM' advantages, the aim of this paper is to extend MM to process the intuitionistic fuzzy numbers (IFNs) and then to solve the multi-attribute group decision making (MAGDM) problems. Firstly, we develop some intuitionistic fuzzy Muirhead mean (IFMM) operators by extending MM to intuitionistic fuzzy information. Then, we prove some properties and discuss some special cases with respect to the parameter vector. Moreover, we present two new methods to deal with MAGDM problems with the intuitionistic fuzzy information based on the proposed MM operators. Finally, we verify the validity and reliability of our methods by using an application example, and analyze the advantages of our methods by comparing with other existing methods.

Family involvement in medical decision-making: Perceptions of nursing and psychology students.

PubMed

Itzhaki, Michal; Hildesheimer, Galya; Barnoy, Sivia; Katz, Michael

2016-05-01

Family members often rely on health care professionals to guide and support them through the decision-making process. Although family involvement in medical decisions should be included in the preservice curriculum for the health care professions, perceptions of students in caring professions on family involvement in medical decision-making have not yet been examined. To examine the perceptions of nursing and psychology students on family involvement in medical decision-making for seriously ill patients. A descriptive cross-sectional design was used. First year undergraduate nursing and psychology students studying for their Bachelor of Arts degree were recruited. Perceptions were assessed with a questionnaire constructed based on the Multi-Attribute Utility Theory (MAUT), which examines decision-maker preferences. The questionnaire consisted of two parts referring to the respondent once as the patient and then as the family caregiver. Questionnaires were completed by 116 nursing students and 156 psychology students. Most were of the opinion that family involvement in decision-making is appropriate, especially when the patient is incapable of making decisions. Nursing students were more inclined than psychology students to think that financial, emotional, and value-based considerations should be part of the family's involvement in decision-making. Both groups of students perceived the emotional consideration as most acceptable, whereas the financial consideration was considered the least acceptable. Nursing and psychology students perceive family involvement in medical decision-making as appropriate. In order to train students to support families in the process of decision-making, further research should examine Shared Decision-Making (SDM) programs, which involve patient and clinician collaboration in health care decisions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis respons to the implementation of nuclear installations safety culture using AHP-TOPSIS

NASA Astrophysics Data System (ADS)

Situmorang, J.; Kuntoro, I.; Santoso, S.; Subekti, M.; Sunaryo, G. R.

2018-02-01

An analysis of responses to the implementation of nuclear installations safety culture has been done using AHP (Analitic Hierarchy Process) - TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). Safety culture is considered as collective commitments of the decision-making level, management level, and individual level. Thus each level will provide a subjective perspective as an alternative approach to implementation. Furthermore safety culture is considered by the statement of five characteristics which in more detail form consist of 37 attributes, and therefore can be expressed as multi-attribute state. Those characteristics and or attributes will be a criterion and its value is difficult to determine. Those criteria of course, will determine and strongly influence the implementation of the corresponding safety culture. To determine the pattern and magnitude of the influence is done by using a TOPSIS that is based on decision matrix approach and is composed of alternatives and criteria. The weight of each criterion is determined by AHP technique. The data used are data collected through questionnaires at the workshop on safety and health in 2015. .Reliability test of data gives Cronbah Alpha value of 95.5% which according to the criteria is stated reliable. Validity test using bivariate correlation analysis technique between each attribute give Pearson correlation for all attribute is significant at level 0,01. Using confirmatory factor analysis gives Kaise-Meyer-Olkin of sampling Adequacy (KMO) is 0.719 and it is greater than the acceptance criterion 0.5 as well as the 0.000 significance level much smaller than 0.05 and stated that further analysis could be performed. As a result of the analysis it is found that responses from the level of decision maker (second echelon) dominate the best order preference rank to be the best solution in strengthening the nuclear installation safety culture, except for the first characteristics, safety is a clearly recognized value. The rank of preference order is obtained sequentially according to the level of policy maker, management and individual or staff.

Decision support framework for evaluating the operational environment of forest bioenergy production and use: Case of four European countries.

PubMed

Pezdevšek Malovrh, Špela; Kurttila, Mikko; Hujala, Teppo; Kärkkäinen, Leena; Leban, Vasja; Lindstad, Berit H; Peters, Dörte Marie; Rhodius, Regina; Solberg, Birger; Wirth, Kristina; Zadnik Stirn, Lidija; Krč, Janez

2016-09-15

Complex policy-making situations around bioenergy production and use require examination of the operational environment of the society and a participatory approach. This paper presents and demonstrates a three-phase decision-making framework for analysing the operational environment of strategies related to increased forest bioenergy targets. The framework is based on SWOT (strengths, weaknesses, opportunities and threats) analysis and the Simple Multi-Attribute Rating Technique (SMART). Stakeholders of four case countries (Finland, Germany, Norway and Slovenia) defined the factors that affect the operational environments, classified in four pre-set categories (Forest Characteristics and Management, Policy Framework, Technology and Science, and Consumers and Society). The stakeholders participated in weighting of SWOT items for two future scenarios with SMART technique. The first scenario reflected the current 2020 targets (the Business-as-Usual scenario), and the second scenario contained a further increase in the targets (the Increase scenario). This framework can be applied to various problems of environmental management and also to other fields where public decision-making is combined with stakeholders' engagement. The case results show that the greatest differences between the scenarios appear in Germany, indicating a notably negative outlook for the Increase scenario, while the smallest differences were found in Finland. Policy Framework was a highly rated category across the countries, mainly with respect to weaknesses and threats. Intensified forest bioenergy harvesting and utilization has potentially wide country-specific impacts which need to be anticipated and considered in national policies and public dialogue. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decision making for Pap testing among Pacific Islander women.

PubMed

Weiss, Jie W; Mouttapa, Michele; Sablan-Santos, Lola; DeGuzman Lacsamana, Jasmine; Quitugua, Lourdes; Park Tanjasiri, Sora

2016-12-01

This study employed a Multi-Attribute Utility (MAU) model to examine the Pap test decision-making process among Pacific Islanders (PI) residing in Southern California. A total of 585 PI women were recruited through social networks from Samoan and Tongan churches, and Chamorro family clans. A questionnaire assessed Pap test knowledge, beliefs and past behaviour. The three MAU parameters of subjective value, subjective probability and momentary salience were measured for eight anticipated consequences of having a Pap test (e.g., feeling embarrassed, spending money). Logistic regression indicated that women who had a Pap test (Pap women) had higher total MAU utility scores compared to women who had not had a Pap test within the past three years (No Pap women) (adjusted Odds Ratio = 1.10). In particular, Pap women had higher utilities for the positive consequences 'Detecting cervical cancer early, Peace of mind, and Protecting my family', compared to No Pap women. It is concluded that the connection between utility and behaviour offers a promising pathway toward a better understanding of the decision to undergo Pap testing. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model

PubMed Central

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals. PMID:27877103

Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making

PubMed Central

Sun, Clement S.; Cantor, Scott B.; Reece, Gregory P.; Crosby, Melissa A.; Fingeret, Michelle C.

2014-01-01

Background: Women considering breast reconstruction must make challenging trade-offs among issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. Methods: In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using 9 different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual well-being as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants’ rankings. Results: The median amount of time required to assess preferences was 34 minutes. Agreement among the 9 preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best-performing risk-averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the 7 attributes. Conclusions: We recommend the risk-averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study. PMID:25105083

Multi-Attribute Selection of Coal Center Location: A Case Study in Thailand

NASA Astrophysics Data System (ADS)

Kuakunrittiwong, T.; Ratanakuakangwan, S.

2016-11-01

Under Power Development Plan 2015, Thailand has to diversify its heavily gas-fired electricity generation. The main owner of electricity transmission grids is responsible to implement several coal-fired power plants with clean coal technology. To environmentally handle and economically transport unprecedented quantities of sub-bituminous and bituminous coal, a coal center is required. The location of such facility is an important strategic decision and a paramount to the success of the energy plan. As site selection involves many criteria, Fuzzy Analytical Hierarchy Process or Fuzzy-AHP is applied to select the most suitable location among three candidates. Having analyzed relevant criteria and the potential alternatives, the result reveals that engineering and socioeconomic are important criteria and Map Ta Phut is the most suitable site for the coal center.

Analysis of Subjective Judgment Matrices.

DTIC Science & Technology

1980-05-01

Matrices.i. Crawford, Gordon, 1936- joint author. 11. Title. Ill Series: Rad Coporation . Rand reports o R-2572-0. A036-.13 R-2572 (E*278.2) 081s (519.5�...scaling the worth of a set of objects or entities . For problems that fit the Saaty framework, this report details aa ImpEuveNeL ua Sd4Ly’b "CtSgeLVCLLuL...Analysis for Siting of Nuclear Plants: The Relevance of Multiattribute Utility Theory ," Technical Report No. 96, Operations Research Center, MIT, 1974. 8

Rooftop greenhouses in educational centers: A sustainability assessment of urban agriculture in compact cities.

PubMed

Nadal, Ana; Pons, Oriol; Cuerva, Eva; Rieradevall, Joan; Josa, Alejandro

2018-06-01

Today, urban agriculture is one of the most widely used sustainability strategies to improve the metabolism of a city. Schools can play an important role in the implementation of sustainability master plans, due their socio-educational activities and their cohesive links with families; all key elements in the development of urban agriculture. Thus, the main objective of this research is to develop a procedure, in compact cities, to assess the potential installation of rooftop greenhouses (RTGs) in schools. The generation of a dynamic assessment tool capable of identifying and prioritizing schools with a high potential for RTGs and their eventual implementation would also represent a significant factor in the environmental, social, and nutritional education of younger generations. The methodology has four-stages (Pre-selection criteria; Selection of necessities; Sustainability analysis; and Sensitivity analysis and selection of the best alternative) in which economic, environmental, social and governance aspects all are considered. It makes use of Multi-Attribute Utility Theory and Multi-Criteria Decision Making, through the Integrated Value Model for Sustainability Assessments and the participation of two panels of multidisciplinary specialists, for the preparation of a unified sustainability index that guarantees the objectivity of the selection process. This methodology has been applied and validated in a case study of 11 schools in Barcelona (Spain). The social perspective of the proposed methodology favored the school in the case-study with the most staff and the largest parent-teacher association (social and governance indicators) that obtained the highest sustainability index (S11); at a considerable distance (45%) from the worst case (S3) with fewer school staff and parental support. Finally, objective decisions may be taken with the assistance of this appropriate, adaptable, and reliable Multi-Criteria Decision-Making tool on the vertical integration and implementation of urban agriculture in schools, in support of the goals of sustainable development and the circular economy. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessment of combating-desertification strategies using the linear assignment method

NASA Astrophysics Data System (ADS)

Hassan Sadeghravesh, Mohammad; Khosravi, Hassan; Ghasemian, Soudeh

2016-04-01

Nowadays desertification, as a global problem, affects many countries in the world, especially developing countries like Iran. With respect to increasing importance of desertification and its complexity, the necessity of attention to the optimal combating-desertification alternatives is essential. Selecting appropriate strategies according to all effective criteria to combat the desertification process can be useful in rehabilitating degraded lands and avoiding degradation in vulnerable fields. This study provides systematic and optimal strategies of combating desertification by use of a group decision-making model. To this end, the preferences of indexes were obtained through using the Delphi model, within the framework of multi-attribute decision making (MADM). Then, priorities of strategies were evaluated by using linear assignment (LA) method. According to the results, the strategies to prevent improper change of land use (A18), development and reclamation of plant cover (A23), and control overcharging of groundwater resources (A31) were identified as the most important strategies for combating desertification in this study area. Therefore, it is suggested that the aforementioned ranking results be considered in projects which control and reduce the effects of desertification and rehabilitate degraded lands.

Integrated Decision-Making Tool to Develop Spent Fuel Strategies for Research Reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beatty, Randy L; Harrison, Thomas J

IAEA Member States operating or having previously operated a Research Reactor are responsible for the safe and sustainable management and disposal of associated radioactive waste, including research reactor spent nuclear fuel (RRSNF). This includes the safe disposal of RRSNF or the corresponding equivalent waste returned after spent fuel reprocessing. One key challenge to developing general recommendations lies in the diversity of spent fuel types, locations and national/regional circumstances rather than mass or volume alone. This is especially true given that RRSNF inventories are relatively small, and research reactors are rarely operated at a high power level or duration typical ofmore » commercial power plants. Presently, many countries lack an effective long-term policy for managing RRSNF. This paper presents results of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) #T33001 on Options and Technologies for Managing the Back End of the Research Reactor Nuclear Fuel Cycle which includes an Integrated Decision Making Tool called BRIDE (Back-end Research reactor Integrated Decision Evaluation). This is a multi-attribute decision-making tool that combines the Total Estimated Cost of each life-cycle scenario with Non-economic factors such as public acceptance, technical maturity etc and ranks optional back-end scenarios specific to member states situations in order to develop a specific member state strategic plan with a preferred or recommended option for managing spent fuel from Research Reactors.« less

Towards the ecotourism: a decision support model for the assessment of sustainability of mountain huts in the Alps.

PubMed

Stubelj Ars, Mojca; Bohanec, Marko

2010-12-01

This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts' surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists. Copyright © 2010 Elsevier Ltd. All rights reserved.

TIES for Dummies 3rd Edition (Technology Identification, Evaluation, and Selection) Basic how to's to implement the TIES method

NASA Technical Reports Server (NTRS)

Kirby, Michelle R.

2002-01-01

The TIES method is a forecasting environment whereby the decision-maker has the ability to easily assess and trade-off the impact of various technologies without sophisticated and time-consuming mathematical formulations. TIES provides a methodical approach where technically feasible alternatives can be identified with accuracy and speed to reduce design cycle time, and subsequently, life cycle costs, and was achieved through the use of various probabilistic methods, such as Response Surface Methodology and Monte Carlo Simulations. Furthermore, structured and systematic techniques are utilized from other fields to identify possible concepts and evaluation criteria by which comparisons can be made. This objective is achieved by employing the use of Morphological Matrices and Multi-Attribute Decision Making techniques. Through the execution of each step, a family of design alternatives for a given set of customer requirements can be identified and assessed subjectively or objectively. This methodology allows for more information (knowledge) to be brought into the earlier phases of the design process and will have direct implications on the affordability of the system. The increased knowledge allows for optimum allocation of company resources and quantitative justification for program decisions. Finally, the TIES method provided novel results and quantitative justification to facilitate decision making in the early stages of design so as to produce affordable and quality products.

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

NASA Astrophysics Data System (ADS)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

A decision support tool for selecting the optimal sewage sludge treatment.

PubMed

Turunen, Ville; Sorvari, Jaana; Mikola, Anna

2018-02-01

Sewage sludge contains significant amounts of resources, such as nutrients and organic matter. At the same time, the organic contaminants (OC) found in sewage sludge are of growing concern. Consequently, in many European countries incineration is currently favored over recycling in agriculture. This study presents a Multi-Attribute Value Theory (MAVT)-based decision support tool (DST) for facilitating sludge treatment decisions. Essential decision criteria were recognized and prioritized, i.e., weighted, by experts from water utilities. Since the fate of organic contaminants was in focus, a simple scoring method was developed to take into account their environmental risks. The final DST assigns each sludge treatment method a preference score expressing its superiority compared to alternative methods. The DST was validated by testing it with data from two Finnish municipal wastewater treatment plants (WWTP). The validation results of the first case study preferred sludge pyrolysis (preference score: 0.629) to other alternatives: composting and incineration (score 0.580, and 0.484 respectively). The preference scores were influenced by WWTP dependent factors, i.e., the operating environment and the weighting of the criteria. A lack of data emerged as the main practical limitation. Therefore, not all of the relevant criteria could be included in the value tree. More data are needed on the effects of treatment methods on the availability of nutrients, the quality of organic matter and sludge-borne OCs. Despite these shortcomings, the DST proved useful and adaptable in decision-making. It can also help achieve a more transparent, understandable and comprehensive decision-making process. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of Low-Latency Obfuscated Traffic Using Multi-Attribute Analysis

DTIC Science & Technology

2017-03-01

the distribution of common Tor packet sizes. Herrmann et al. also contend that the remaining variations in observed packet sizes are caused by OS...specific fragmentation and that Tor’s variation in packet size provides an additional level of protection as the false positive rate (FPR) using packet...three pre-filter variations , the observed FPR for non-Tor ranged from 94.4 percent to 7.2 percent, and the observed FNR for Tor ranged from 61.3

Evaluative methodology for prioritizing transportation energy conservation strategies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pang, L.M.G.

An analytical methodology was developed for the purpose of prioritizing a set of transportation energy conservation (TEC) strategies within an urban environment. Steps involved in applying the methodology consist of 1) defining the goals, objectives and constraints of the given urban community, 2) identifying potential TEC strategies, 3) assessing the impact of the strategies, 4) applying the TEC evaluation model, and 5) utilizing a selection process to determine the optimal set of strategies for implementation. This research provides an overview of 21 TEC strategies, a quick-response technique for estimating energy savings, a multiattribute utility theory approach for assessing subjective impacts,more » and a computer program for making the strategy evaluations, all of which assist in expediting the execution of the entire methodology procedure. The critical element of the methodology is the strategy evaluation model which incorporates a number of desirable concepts including 1) a comprehensive accounting of all relevant impacts, 2) the application of multiobjective decision-making techniques, 3) an approach to assure compatibilty among quantitative and qualitative impact measures, 4) the inclusion of the decision maker's preferences in the evaluation procedure, and 5) the cost-effectiveness concept. Application of the methodolgy to Salt Lake City, Utah demonstrated its utility, ease of use and favorability by decision makers.« less

Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2017-12-01

Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case studies to highlight how Cloud CI streamlines the process for setting up an interactive decision support system. Moreover, advances in artificial intelligence offer new techniques for old problems from integrating data to adaptive sensing or from interactive dashboards to optimizing multi-attribute problems. The combination of scientific expertise, flexible cloud computing solutions, and intelligent systems opens new research horizons.

Building a picture: Prioritisation of exotic diseases for the pig industry in Australia using multi-criteria decision analysis.

PubMed

Brookes, V J; Hernández-Jover, M; Cowled, B; Holyoake, P K; Ward, M P

2014-01-01

Diseases that are exotic to the pig industry in Australia were prioritised using a multi-criteria decision analysis framework that incorporated weights of importance for a range of criteria important to industry stakeholders. Measurements were collected for each disease for nine criteria that described potential disease impacts. A total score was calculated for each disease using a weighted sum value function that aggregated the nine disease criterion measurements and weights of importance for the criteria that were previously elicited from two groups of industry stakeholders. One stakeholder group placed most value on the impacts of disease on livestock, and one group placed more value on the zoonotic impacts of diseases. Prioritisation lists ordered by disease score were produced for both of these groups. Vesicular diseases were found to have the highest priority for the group valuing disease impacts on livestock, followed by acute forms of African and classical swine fever, then highly pathogenic porcine reproductive and respiratory syndrome. The group who valued zoonotic disease impacts prioritised rabies, followed by Japanese encephalitis, Eastern equine encephalitis and Nipah virus, interspersed with vesicular diseases. The multi-criteria framework used in this study systematically prioritised diseases using a multi-attribute theory based technique that provided transparency and repeatability in the process. Flexibility of the framework was demonstrated by aggregating the criterion weights from more than one stakeholder group with the disease measurements for the criteria. This technique allowed industry stakeholders to be active in resource allocation for their industry without the need to be disease experts. We believe it is the first prioritisation of livestock diseases using values provided by industry stakeholders. The prioritisation lists will be used by industry stakeholders to identify diseases for further risk analysis and disease spread modelling to understand biosecurity risks to this industry. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of 3-D graphics software: A case study

NASA Technical Reports Server (NTRS)

Lores, M. E.; Chasen, S. H.; Garner, J. M.

1984-01-01

An efficient 3-D geometry graphics software package which is suitable for advanced design studies was developed. The advanced design system is called GRADE--Graphics for Advanced Design. Efficiency and ease of use are gained by sacrificing flexibility in surface representation. The immediate options were either to continue development of GRADE or to acquire a commercially available system which would replace or complement GRADE. Test cases which would reveal the ability of each system to satisfy the requirements were developed. A scoring method which adequately captured the relative capabilities of the three systems was presented. While more complex multi-attribute decision methods could be used, the selected method provides all the needed information without being so complex that it is difficult to understand. If the value factors are modestly perturbed, system Z is a clear winner based on its overall capabilities. System Z is superior in two vital areas: surfacing and ease of interface with application programs.

Using multi-attribute decision-making approaches in the selection of a hospital management system.

PubMed

Arasteh, Mohammad Ali; Shamshirband, Shahaboddin; Yee, Por Lip

2018-01-01

The most appropriate organizational software is always a real challenge for managers, especially, the IT directors. The illustration of the term "enterprise software selection", is to purchase, create, or order a software that; first, is best adapted to require of the organization; and second, has suitable price and technical support. Specifying selection criteria and ranking them, is the primary prerequisite for this action. This article provides a method to evaluate, rank, and compare the available enterprise software for choosing the apt one. The prior mentioned method is constituted of three-stage processes. First, the method identifies the organizational requires and assesses them. Second, it selects the best method throughout three possibilities; indoor-production, buying software, and ordering special software for the native use. Third, the method evaluates, compares and ranks the alternative software. The third process uses different methods of multi attribute decision making (MADM), and compares the consequent results. Based on different characteristics of the problem; several methods had been tested, namely, Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Elimination and Choice Expressing Reality (ELECTURE), and easy weight method. After all, we propose the most practical method for same problems.

Multiattribute health utility scoring for the computerized adaptive measure CAT-5D-QOL was developed and validated.

PubMed

Kopec, Jacek A; Sayre, Eric C; Rogers, Pamela; Davis, Aileen M; Badley, Elizabeth M; Anis, Aslam H; Abrahamowicz, Michal; Russell, Lara; Rahman, Md Mushfiqur; Esdaile, John M

2015-10-01

The CAT-5D-QOL is a previously reported item response theory (IRT)-based computerized adaptive tool to measure five domains (attributes) of health-related quality of life. The objective of this study was to develop and validate a multiattribute health utility (MAHU) scoring method for this instrument. The MAHU scoring system was developed in two stages. In phase I, we obtained standard gamble (SG) utilities for 75 hypothetical health states in which only one domain varied (15 states per domain). In phase II, we obtained SG utilities for 256 multiattribute states. We fit a multiplicative regression model to predict SG utilities from the five IRT domain scores. The prediction model was constrained using data from phase I. We validated MAHU scores by comparing them with the Health Utilities Index Mark 3 (HUI3) and directly measured utilities and by assessing between-group discrimination. MAHU scores have a theoretical range from -0.842 to 1. In the validation study, the scores were, on average, higher than HUI3 utilities and lower than directly measured SG utilities. MAHU scores correlated strongly with the HUI3 (Spearman ρ = 0.78) and discriminated well between groups expected to differ in health status. Results reported here provide initial evidence supporting the validity of the MAHU scoring system for the CAT-5D-QOL. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrated continuous bioprocessing: Economic, operational, and environmental feasibility for clinical and commercial antibody manufacture

PubMed Central

Pollock, James; Coffman, Jon; Ho, Sa V.

2017-01-01

This paper presents a systems approach to evaluating the potential of integrated continuous bioprocessing for monoclonal antibody (mAb) manufacture across a product's lifecycle from preclinical to commercial manufacture. The economic, operational, and environmental feasibility of alternative continuous manufacturing strategies were evaluated holistically using a prototype UCL decisional tool that integrated process economics, discrete‐event simulation, environmental impact analysis, operational risk analysis, and multiattribute decision‐making. The case study focused on comparing whole bioprocesses that used either batch, continuous or a hybrid combination of batch and continuous technologies for cell culture, capture chromatography, and polishing chromatography steps. The cost of goods per gram (COG/g), E‐factor, and operational risk scores of each strategy were established across a matrix of scenarios with differing combinations of clinical development phase and company portfolio size. The tool outputs predict that the optimal strategy for early phase production and small/medium‐sized companies is the integrated continuous strategy (alternating tangential flow filtration (ATF) perfusion, continuous capture, continuous polishing). However, the top ranking strategy changes for commercial production and companies with large portfolios to the hybrid strategy with fed‐batch culture, continuous capture and batch polishing from a COG/g perspective. The multiattribute decision‐making analysis highlighted that if the operational feasibility was considered more important than the economic benefits, the hybrid strategy would be preferred for all company scales. Further considerations outside the scope of this work include the process development costs required to adopt continuous processing. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:854–866, 2017 PMID:28480535

A methodology for the comparative evaluation of alternative bioseparation technologies.

PubMed

Tran, Richard; Zhou, Yuhong; Lacki, Karol M; Titchener-Hooker, Nigel J

2008-01-01

Advances in upstream technologies and growing commercial demand have led to cell culture processes of ever larger volumes and expressing at higher product titers. This has increased the burden on downstream processing. Concerns regarding the capacity limitations of packed-bed chromatography have led process engineers to begin investigating new bioseparation techniques that may be considered as "alternatives" to chromatography, and which could potentially offer higher processing capacities but at a lower cost. With the wide range of alternatives, which are currently available, each with their own strengths and inherent limitations, coupled with the time pressures associated with process development, the challenge for process engineers is to determine which technologies are most worth investigating. This article presents a methodology based on a multiattribute decision making (MADM) analysis approach, utilizing both quantitative and qualitative data, which can be used to determine the "industrial attractiveness" of bioseparation technologies, accounting for trade-offs between their strengths and weaknesses. By including packed-bed chromatography in the analysis as a reference point, it was possible to determine the alternatives, which show the most promise for use in large-scale manufacturing processes. The results of this analysis show that although the majority of alternative techniques offer certain advantages over conventional packed-bed chromatography, their attractiveness overall means that currently none of these technologies may be considered as viable alternatives to chromatography. The methodology introduced in this study may be used to gain significant quantitative insight as to the key areas in which improvements are required for each technique, and thus may be used as a tool to aid in further technological development.

A method for scenario-based risk assessment for robust aerospace systems

NASA Astrophysics Data System (ADS)

Thomas, Victoria Katherine

In years past, aircraft conceptual design centered around creating a feasible aircraft that could be built and could fly the required missions. More recently, aircraft viability entered into conceptual design, allowing that the product's potential to be profitable should also be examined early in the design process. While examining an aerospace system's feasibility and viability early in the design process is extremely important, it is also important to examine system risk. In traditional aerospace systems risk analysis, risk is examined from the perspective of performance, schedule, and cost. Recently, safety and reliability analysis have been brought forward in the design process to also be examined during late conceptual and early preliminary design. While these analyses work as designed, existing risk analysis methods and techniques are not designed to examine an aerospace system's external operating environment and the risks present there. A new method has been developed here to examine, during the early part of concept design, the risk associated with not meeting assumptions about the system's external operating environment. The risks are examined in five categories: employment, culture, government and politics, economics, and technology. The risks are examined over a long time-period, up to the system's entire life cycle. The method consists of eight steps over three focus areas. The first focus area is Problem Setup. During problem setup, the problem is defined and understood to the best of the decision maker's ability. There are four steps in this area, in the following order: Establish the Need, Scenario Development, Identify Solution Alternatives, and Uncertainty and Risk Identification. There is significant iteration between steps two through four. Focus area two is Modeling and Simulation. In this area the solution alternatives and risks are modeled, and a numerical value for risk is calculated. A risk mitigation model is also created. The four steps involved in completing the modeling and simulation are: Alternative Solution Modeling, Uncertainty Quantification, Risk Assessment, and Risk Mitigation. Focus area three consists of Decision Support. In this area a decision support interface is created that allows for game playing between solution alternatives and risk mitigation. A multi-attribute decision making process is also implemented to aid in decision making. A demonstration problem inspired by Airbus' mid 1980s decision to break into the widebody long-range market was developed to illustrate the use of this method. The results showed that the method is able to capture additional types of risk than previous analysis methods, particularly at the early stages of aircraft design. It was also shown that the method can be used to help create a system that is robust to external environmental factors. The addition of an external environment risk analysis in the early stages of conceptual design can add another dimension to the analysis of feasibility and viability. The ability to take risk into account during the early stages of the design process can allow for the elimination of potentially feasible and viable but too-risky alternatives. The addition of a scenario-based analysis instead of a traditional probabilistic analysis enabled uncertainty to be effectively bound and examined over a variety of potential futures instead of only a single future. There is also potential for a product to be groomed for a specific future that one believes is likely to happen, or for a product to be steered during design as the future unfolds.

Minimizing Erosion and Agro-Pollutants Transport from Furrow Irrigated Fields to the Nearby Water Body Using Spatially-Explicit Agent Based Model and Decision Optimization Platform

NASA Astrophysics Data System (ADS)

Ghoveisi, H.; Al Dughaishi, U.; Kiker, G.

2017-12-01

Maintaining water quality in agricultural watersheds is a worldwide challenge, especially where furrow irrigation is being practiced. The Yakima River Basin watershed in south central Washington State, (USA) is an example of these impacted areas with elevated load of sediments and other agricultural products due to runoff from furrow-irrigated fields. Within the Yakima basin, the Granger Drain watershed (area of 75 km2) is particularly challenged in this regard with more than 400 flood-irrigated individual parcels (area of 21 km2) growing a variety of crops from maize to grapes. Alternatives for improving water quality from furrow-irrigated parcels include vegetated filter strip (VFS) implementation, furrow water application efficiency, polyacrylamide (PAM) application and irrigation scheduling. These alternatives were simulated separately and in combinations to explore potential Best Management Practices (BMPs) for runoff-related-pollution reduction in a spatially explicit, agent based modeling system (QnD:GrangerDrain). Two regulatory scenarios were tested to BMP adoption within individual parcels. A blanket-style regulatory scenario simulated a total of 60 BMP combinations implemented in all 409 furrow-irrigated parcels. A second regulatory scenario simulated the BMPs in 119 furrow-irrigated parcels designated as "hotspots" based on a standard 12 Mg ha-1 seasonal sediment load. The simulated cumulative runoff and sediment loading from all BMP alternatives were ranked using Multiple Criteria Decision Analysis (MCDA), specifically the Stochastic Multi-Attribute Acceptability Analysis (SMAA) method. Several BMP combinations proved successful in reducing loads below a 25 NTU (91 mg L-1) regulatory sediment concentration. The QnD:GrangerDrain simulations and subsequent MCDA ranking revealed that the BMP combinations of 5 m-VFS and high furrow water efficiency were highly ranked alternatives for both the blanket and hotspot scenarios.

The Multi-Attribute Task Battery II (MATB-II) Software for Human Performance and Workload Research: A User's Guide

NASA Technical Reports Server (NTRS)

Santiago-Espada, Yamira; Myer, Robert R.; Latorella, Kara A.; Comstock, James R., Jr.

2011-01-01

The Multi-Attribute Task Battery (MAT Battery). is a computer-based task designed to evaluate operator performance and workload, has been redeveloped to operate in Windows XP Service Pack 3, Windows Vista and Windows 7 operating systems.MATB-II includes essentially the same tasks as the original MAT Battery, plus new configuration options including a graphical user interface for controlling modes of operation. MATB-II can be executed either in training or testing mode, as defined by the MATB-II configuration file. The configuration file also allows set up of the default timeouts for the tasks, the flow rates of the pumps and tank levels of the Resource Management (RESMAN) task. MATB-II comes with a default event file that an experimenter can modify and adapt

Estimation of a Preference-Based Summary Score for the Patient-Reported Outcomes Measurement Information System: The PROMIS®-Preference (PROPr) Scoring System.

PubMed

Dewitt, Barry; Feeny, David; Fischhoff, Baruch; Cella, David; Hays, Ron D; Hess, Rachel; Pilkonis, Paul A; Revicki, Dennis A; Roberts, Mark S; Tsevat, Joel; Yu, Lan; Hanmer, Janel

2018-06-01

Health-related quality of life (HRQL) preference-based scores are used to assess the health of populations and patients and for cost-effectiveness analyses. The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS ® ) consists of patient-reported outcome measures developed using item response theory. PROMIS is in need of a direct preference-based scoring system for assigning values to health states. To produce societal preference-based scores for 7 PROMIS domains: Cognitive Function-Abilities, Depression, Fatigue, Pain Interference, Physical Function, Sleep Disturbance, and Ability to Participate in Social Roles and Activities. Online survey of a US nationally representative sample ( n = 983). Preferences for PROMIS health states were elicited with the standard gamble to obtain both single-attribute scoring functions for each of the 7 PROMIS domains and a multiplicative multiattribute utility (scoring) function. The 7 single-attribute scoring functions were fit using isotonic regression with linear interpolation. The multiplicative multiattribute summary function estimates utilities for PROMIS multiattribute health states on a scale where 0 is the utility of being dead and 1 the utility of "full health." The lowest possible score is -0.022 (for a state viewed as worse than dead), and the highest possible score is 1. The online survey systematically excludes some subgroups, such as the visually impaired and illiterate. A generic societal preference-based scoring system is now available for all studies using these 7 PROMIS health domains.

Evaluating the Role of Attention in the Context of Unconscious Thought Theory: Differential Impact of Attentional Scope and Load on Preference and Memory

PubMed Central

Srinivasan, Narayanan; Mukherjee, Sumitava; Mishra, Maruti V.; Kesarwani, Smriti

2013-01-01

Attention is a key process used to conceptualize and define modes of thought, but we lack information about the role of specific attentional processes on preferential choice and memory in multi-attribute decision making. In this study, we examine the role of attention based on two dimensions, attentional scope and load on choice preference strength and memory using a paradigm that arguably elicits unconscious thought. Scope of attention was manipulated by using global or local processing during distraction (Experiment 1) and before the information-encoding stage (Experiment 2). Load was manipulated by using the n-back task in Experiment 1. Results from Experiment 1 show that global processing or distributed attention during distraction results in stronger preference irrespective of load but better memory only at low cognitive load. Task difficulty or load did not have any effect on preference or memory. In Experiment 2, distributed attention before attribute encoding facilitated only memory but did not influence preference. Results show that attentional processes at different stages of processing like distraction and information-encoding influence decision making processes. Scope of attention not only influences preference and memory but the manner in which attentional scope influences them depends on both load and stage of information processing. The results indicate the important role of attention in processes critical for decision making and calls for a re-evaluation of the unconscious thought theory (UTT) and the need for reconceptualizing the role of attention. PMID:23382726

Evaluating the role of attention in the context of unconscious thought theory: differential impact of attentional scope and load on preference and memory.

PubMed

Srinivasan, Narayanan; Mukherjee, Sumitava; Mishra, Maruti V; Kesarwani, Smriti

2013-01-01

Attention is a key process used to conceptualize and define modes of thought, but we lack information about the role of specific attentional processes on preferential choice and memory in multi-attribute decision making. In this study, we examine the role of attention based on two dimensions, attentional scope and load on choice preference strength and memory using a paradigm that arguably elicits unconscious thought. Scope of attention was manipulated by using global or local processing during distraction (Experiment 1) and before the information-encoding stage (Experiment 2). Load was manipulated by using the n-back task in Experiment 1. Results from Experiment 1 show that global processing or distributed attention during distraction results in stronger preference irrespective of load but better memory only at low cognitive load. Task difficulty or load did not have any effect on preference or memory. In Experiment 2, distributed attention before attribute encoding facilitated only memory but did not influence preference. Results show that attentional processes at different stages of processing like distraction and information-encoding influence decision making processes. Scope of attention not only influences preference and memory but the manner in which attentional scope influences them depends on both load and stage of information processing. The results indicate the important role of attention in processes critical for decision making and calls for a re-evaluation of the unconscious thought theory (UTT) and the need for reconceptualizing the role of attention.

Decision heuristic or preference? Attribute non-attendance in discrete choice problems.

PubMed

Heidenreich, Sebastian; Watson, Verity; Ryan, Mandy; Phimister, Euan

2018-01-01

This paper investigates if respondents' choice to not consider all characteristics of a multiattribute health service may represent preferences. Over the last decade, an increasing number of studies account for attribute non-attendance (ANA) when using discrete choice experiments to elicit individuals' preferences. Most studies assume such behaviour is a heuristic and therefore uninformative. This assumption may result in misleading welfare estimates if ANA reflects preferences. This is the first paper to assess if ANA is a heuristic or genuine preference without relying on respondents' self-stated motivation and the first study to explore this question within a health context. Based on findings from cognitive psychology, we expect that familiar respondents are less likely to use a decision heuristic to simplify choices than unfamiliar respondents. We employ a latent class model of discrete choice experiment data concerned with National Health Service managers' preferences for support services that assist with performance concerns. We present quantitative and qualitative evidence that in our study ANA mostly represents preferences. We also show that wrong assumptions about ANA result in inadequate welfare measures that can result in suboptimal policy advice. Future research should proceed with caution when assuming that ANA is a heuristic. Copyright © 2017 John Wiley & Sons, Ltd.

A synoptic description of coal basins via image processing

NASA Technical Reports Server (NTRS)

Farrell, K. W., Jr.; Wherry, D. B.

1978-01-01

An existing image processing system is adapted to describe the geologic attributes of a regional coal basin. This scheme handles a map as if it were a matrix, in contrast to more conventional approaches which represent map information in terms of linked polygons. The utility of the image processing approach is demonstrated by a multiattribute analysis of the Herrin No. 6 coal seam in Illinois. Findings include the location of a resource and estimation of tonnage corresponding to constraints on seam thickness, overburden, and Btu value, which are illustrative of the need for new mining technology.

Multi-agent framework for negotiation in a closed environment

NASA Astrophysics Data System (ADS)

Cretan, Adina; Coutinho, Carlos; Bratu, Ben; Jardim-Goncalves, Ricardo

2013-10-01

The goal of this paper is to offer support for small and medium enterprises which cannot or do not want to fulfill a big contract alone. Each organization has limited resources and in order to better accomplish a higher external demand, the managers are forced to outsource parts of their contracts even to concurrent organizations. In this concurrent environment each enterprise wants to preserve its decision autonomy and to disclose as little as possible from its business information. To describe this interaction, our approach is to define a framework for managing parallel and concurrent negotiations among independent organizations acting in the same industrial market. The complexity of our negotiation framework is done by the dynamic environment in which multi-attribute and multi-participant negotiations are racing over the same set of resources. Moreover, the proposed framework helps the organizations within the collaborative networked environment to augment their efficiency and ability to react to unforeseen situations, thus improving their market competitiveness.

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cetiner, Sacit M; Kisner, Roger A; Muhlheim, Michael David

2015-07-01

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or nomore » human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.« less

Max-margin multiattribute learning with low-rank constraint.

PubMed

Zhang, Qiang; Chen, Lin; Li, Baoxin

2014-07-01

Attribute learning has attracted a lot of interests in recent years for its advantage of being able to model high-level concepts with a compact set of midlevel attributes. Real-world objects often demand multiple attributes for effective modeling. Most existing methods learn attributes independently without explicitly considering their intrinsic relatedness. In this paper, we propose max margin multiattribute learning with low-rank constraint, which learns a set of attributes simultaneously, using only relative ranking of the attributes for the data. By learning all the attributes simultaneously through low-rank constraint, the proposed method is able to capture their intrinsic correlation for improved learning; by requiring only relative ranking, the method avoids restrictive binary labels of attributes that are often assumed by many existing techniques. The proposed method is evaluated on both synthetic data and real visual data including a challenging video data set. Experimental results demonstrate the effectiveness of the proposed method.

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

PubMed

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

Facies Modeling Using 3D Pre-Stack Simultaneous Seismic Inversion and Multi-Attribute Probability Neural Network Transform in the Wattenberg Field, Colorado

NASA Astrophysics Data System (ADS)

Harryandi, Sheila

The Niobrara/Codell unconventional tight reservoir play at Wattenberg Field, Colorado has potentially two billion barrels of oil equivalent requiring hundreds of wells to access this resource. The Reservoir Characterization Project (RCP), in conjunction with Anadarko Petroleum Corporation (APC), began reservoir characterization research to determine how to increase reservoir recovery while maximizing operational efficiency. Past research results indicate that targeting the highest rock quality within the reservoir section for hydraulic fracturing is optimal for improving horizontal well stimulation through multi-stage hydraulic fracturing. The reservoir is highly heterogeneous, consisting of alternating chalks and marls. Modeling the facies within the reservoir is very important to be able to capture the heterogeneity at the well-bore scale; this heterogeneity is then upscaled from the borehole scale to the seismic scale to distribute the heterogeneity in the inter-well space. I performed facies clustering analysis to create several facies defining the reservoir interval in the RCP Wattenberg Field study area. Each facies can be expressed in terms of a range of rock property values from wells obtained by cluster analysis. I used the facies classification from the wells to guide the pre-stack seismic inversion and multi-attribute transform. The seismic data extended the facies information and rock quality information from the wells. By obtaining this information from the 3D facies model, I generated a facies volume capturing the reservoir heterogeneity throughout a ten square mile study-area within the field area. Recommendations are made based on the facies modeling, which include the location for future hydraulic fracturing/re-fracturing treatments to improve recovery from the reservoir, and potential deeper intervals for future exploration drilling targets.

Why do multi-attribute utility instruments produce different utilities: the relative importance of the descriptive systems, scale and 'micro-utility' effects.

PubMed

Richardson, Jeff; Iezzi, Angelo; Khan, Munir A

2015-08-01

Health state utilities measured by the major multi-attribute utility instruments differ. Understanding the reasons for this is important for the choice of instrument and for research designed to reconcile these differences. This paper investigates these reasons by explaining pairwise differences between utilities derived from six multi-attribute utility instruments in terms of (1) their implicit measurement scales; (2) the structure of their descriptive systems; and (3) 'micro-utility effects', scale-adjusted differences attributable to their utility formula. The EQ-5D-5L, SF-6D, HUI 3, 15D and AQoL-8D were administered to 8,019 individuals. Utilities and unweighted values were calculated using each instrument. Scale effects were determined by the linear relationship between utilities, the effect of the descriptive system by comparison of scale-adjusted values and 'micro-utility effects' by the unexplained difference between utilities and values. Overall, 66 % of the differences between utilities was attributable to the descriptive systems, 30.3 % to scale effects and 3.7 % to micro-utility effects. Results imply that the revision of utility algorithms will not reconcile differences between instruments. The dominating importance of the descriptive system highlights the need for researchers to select the instrument most capable of describing the health states relevant for a study. Reconciliation of inconsistent utilities produced by different instruments must focus primarily upon the content of the descriptive system. Utility weights primarily determine the measurement scale. Other differences, attributable to utility formula, are comparatively unimportant.

Multiattribute probabilistic prostate elastic registration (MAPPER): Application to fusion of ultrasound and magnetic resonance imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sparks, Rachel, E-mail: rachel.sparks@ucl.ac.uk; Barratt, Dean; Nicolas Bloch, B.

2015-03-15

Purpose: Transrectal ultrasound (TRUS)-guided needle biopsy is the current gold standard for prostate cancer diagnosis. However, up to 40% of prostate cancer lesions appears isoechoic on TRUS. Hence, TRUS-guided biopsy has a high false negative rate for prostate cancer diagnosis. Magnetic resonance imaging (MRI) is better able to distinguish prostate cancer from benign tissue. However, MRI-guided biopsy requires special equipment and training and a longer procedure time. MRI-TRUS fusion, where MRI is acquired preoperatively and then aligned to TRUS, allows for advantages of both modalities to be leveraged during biopsy. MRI-TRUS-guided biopsy increases the yield of cancer positive biopsies. Inmore » this work, the authors present multiattribute probabilistic postate elastic registration (MAPPER) to align prostate MRI and TRUS imagery. Methods: MAPPER involves (1) segmenting the prostate on MRI, (2) calculating a multiattribute probabilistic map of prostate location on TRUS, and (3) maximizing overlap between the prostate segmentation on MRI and the multiattribute probabilistic map on TRUS, thereby driving registration of MRI onto TRUS. MAPPER represents a significant advancement over the current state-of-the-art as it requires no user interaction during the biopsy procedure by leveraging texture and spatial information to determine the prostate location on TRUS. Although MAPPER requires manual interaction to segment the prostate on MRI, this step is performed prior to biopsy and will not substantially increase biopsy procedure time. Results: MAPPER was evaluated on 13 patient studies from two independent datasets—Dataset 1 has 6 studies acquired with a side-firing TRUS probe and a 1.5 T pelvic phased-array coil MRI; Dataset 2 has 7 studies acquired with a volumetric end-firing TRUS probe and a 3.0 T endorectal coil MRI. MAPPER has a root-mean-square error (RMSE) for expert selected fiducials of 3.36 ± 1.10 mm for Dataset 1 and 3.14 ± 0.75 mm for Dataset 2. State-of-the-art MRI-TRUS fusion methods report RMSE of 3.06–2.07 mm. Conclusions: MAPPER aligns MRI and TRUS imagery without manual intervention ensuring efficient, reproducible registration. MAPPER has a similar RMSE to state-of-the-art methods that require manual intervention.« less

Integrated Risk-Informed Decision-Making for an ALMR PRISM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muhlheim, Michael David; Belles, Randy; Denning, Richard S.

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace ormore » supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.« less

A Generalized Measurement Model to Quantify Health: The Multi-Attribute Preference Response Model

PubMed Central

Krabbe, Paul F. M.

2013-01-01

After 40 years of deriving metric values for health status or health-related quality of life, the effective quantification of subjective health outcomes is still a challenge. Here, two of the best measurement tools, the discrete choice and the Rasch model, are combined to create a new model for deriving health values. First, existing techniques to value health states are briefly discussed followed by a reflection on the recent revival of interest in patients’ experience with regard to their possible role in health measurement. Subsequently, three basic principles for valid health measurement are reviewed, namely unidimensionality, interval level, and invariance. In the main section, the basic operation of measurement is then discussed in the framework of probabilistic discrete choice analysis (random utility model) and the psychometric Rasch model. It is then shown how combining the main features of these two models yields an integrated measurement model, called the multi-attribute preference response (MAPR) model, which is introduced here. This new model transforms subjective individual rank data into a metric scale using responses from patients who have experienced certain health states. Its measurement mechanism largely prevents biases such as adaptation and coping. Several extensions of the MAPR model are presented. The MAPR model can be applied to a wide range of research problems. If extended with the self-selection of relevant health domains for the individual patient, this model will be more valid than existing valuation techniques. PMID:24278141

A MULTI-ATTRIBUTE APPROACH TO RISK PRIORITIZATION. (R827920)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Multi-Attribute Task Battery - Applications in pilot workload and strategic behavior research

NASA Technical Reports Server (NTRS)

Arnegard, Ruth J.; Comstock, J. R., Jr.

1991-01-01

The Multi-Attribute Task (MAT) Battery provides a benchmark set of tasks for use in a wide range of lab studies of operator performance and workload. The battery incorporates tasks analogous to activities that aircraft crewmembers perform in flight, while providing a high degree of experimenter control, performance data on each subtask, and freedom to nonpilot test subjects. Features not found in existing computer based tasks include an auditory communication task (to simulate Air Traffic Control communication), a resource management task permitting many avenues or strategies of maintaining target performance, a scheduling window which gives the operator information about future task demands, and the option of manual or automated control of tasks. Performance data are generated for each subtask. In addition, the task battery may be paused and onscreen workload rating scales presented to the subject. The MAT Battery requires a desktop computer with color graphics. The communication task requires a serial link to a second desktop computer with a voice synthesizer or digitizer card.

The multi-attribute task battery for human operator workload and strategic behavior research

NASA Technical Reports Server (NTRS)

Comstock, J. Raymond, Jr.; Arnegard, Ruth J.

1992-01-01

The Multi-Attribute Task (MAT) Battery provides a benchmark set of tasks for use in a wide range of lab studies of operator performance and workload. The battery incorporates tasks analogous to activities that aircraft crewmembers perform in flight, while providing a high degree of experimenter control, performance data on each subtask, and freedom to use nonpilot test subjects. Features not found in existing computer based tasks include an auditory communication task (to simulate Air Traffic Control communication), a resource management task permitting many avenues or strategies of maintaining target performance, a scheduling window which gives the operator information about future task demands, and the option of manual or automated control of tasks. Performance data are generated for each subtask. In addition, the task battery may be paused and onscreen workload rating scales presented to the subject. The MAT Battery requires a desktop computer with color graphics. The communication task requires a serial link to a second desktop computer with a voice synthesizer or digitizer card.

[Application of multiple-attribute utility technology (MAUT) to decisions about a work-site stress-control intervention for public-sector office workers].

PubMed

Hagihara, Akihito; Tarumi, Kimio

2013-01-01

The reasons behind the establishment of particular health-promotion programs in community or work settings are often unclear, and such programs are rarely evaluated from a broad perspective after they are implemented. Thus, multiattribute utility technology (MAUT) was used to design a work-site stress-control program. The sample consisted of public-sector workers in B City in Japan. Stakeholders in the work-site stress-control program included employers (municipal authorities), employees (public workers), and healthcare personnel. Six goals and three strategies (i.e., personnel, self-care, and staff) related to stress-control programs were considered. The results showed that the self-care strategy received the highest score for overall utility (i.e., 96.2), and the overall-utility score for the remaining two strategies was approximately 70. The self-care strategy emerged as the most useful of the three strategies for developing a stress-control program in a target work place. The application of MAUT may be useful for developing an effective stress-control program in occupational settings.

Eye Movements in Strategic Choice

PubMed Central

Gächter, Simon; Noguchi, Takao; Mullett, Timothy L.

2015-01-01

Abstract In risky and other multiattribute choices, the process of choosing is well described by random walk or drift diffusion models in which evidence is accumulated over time to threshold. In strategic choices, level‐k and cognitive hierarchy models have been offered as accounts of the choice process, in which people simulate the choice processes of their opponents or partners. We recorded the eye movements in 2 × 2 symmetric games including dominance‐solvable games like prisoner's dilemma and asymmetric coordination games like stag hunt and hawk–dove. The evidence was most consistent with the accumulation of payoff differences over time: we found longer duration choices with more fixations when payoffs differences were more finely balanced, an emerging bias to gaze more at the payoffs for the action ultimately chosen, and that a simple count of transitions between payoffs—whether or not the comparison is strategically informative—was strongly associated with the final choice. The accumulator models do account for these strategic choice process measures, but the level‐k and cognitive hierarchy models do not. © 2015 The Authors. Journal of Behavioral Decision Making published by John Wiley & Sons Ltd. PMID:27513881

Implementing interactive decision support: A case for combining cyberinfrastructure, data fusion, and social process to mobilize scientific knowledge in sustainability problems

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2014-12-01

Geosciences are becoming increasingly data intensive, particularly in relation to sustainability problems, which are multi-dimensional, weakly structured and characterized by high levels of uncertainty. In the case of complex resource management problems, the challenge is to extract meaningful information from data and make sense of it. Simultaneously, scientific knowledge alone is insufficient to change practice. Creating tools, and group decision support processes for end users to interact with data are key challenges to transforming science-based information into actionable knowledge. The ENCOMPASS project began as a multi-year case study in the Atacama Desert of Chile to design and implement a knowledge transfer model for energy-water-mining conflicts in the region. ENCOMPASS combines the use of cyberinfrastructure (CI), automated data collection, interactive interfaces for dynamic decision support, and participatory modelling to support social learning. A pilot version of the ENCOMPASS CI uses open source systems and serves as a structure to integrate and store multiple forms of data and knowledge, such as DEM, meteorological, water quality, geomicrobiological, energy demand, and groundwater models. In the case study, informatics and data fusion needs related to scientific uncertainty around deep groundwater flowpaths and energy-water connections. Users may upload data from field sites with handheld devices or desktops. Once uploaded, data assets are accessible for a variety of uses. To address multi-attributed decision problems in the Atacama region a standalone application with touch-enabled interfaces was created to improve real-time interactions with datasets by groups. The tool was used to merge datasets from the ENCOMPASS CI to support exploration among alternatives and build shared understanding among stakeholders. To date, the project has increased technical capacity among stakeholders, resulted in the creation of both for-profit and non-profit entities, enabled cross-sector collaboration with mining-indigenous stakeholders, and produced an interactive application for group decision support. ENCOMPASS leverages advances in computational tools to deliver data and models for group decision support applied to sustainability science problems.

Personalized treatment planning with a model of radiation therapy outcomes for use in multiobjective optimization of IMRT plans for prostate cancer.

PubMed

Smith, Wade P; Kim, Minsun; Holdsworth, Clay; Liao, Jay; Phillips, Mark H

2016-03-11

To build a new treatment planning approach that extends beyond radiation transport and IMRT optimization by modeling the radiation therapy process and prognostic indicators for more outcome-focused decision making. An in-house treatment planning system was modified to include multiobjective inverse planning, a probabilistic outcome model, and a multi-attribute decision aid. A genetic algorithm generated a set of plans embodying trade-offs between the separate objectives. An influence diagram network modeled the radiation therapy process of prostate cancer using expert opinion, results of clinical trials, and published research. A Markov model calculated a quality adjusted life expectancy (QALE), which was the endpoint for ranking plans. The Multiobjective Evolutionary Algorithm (MOEA) was designed to produce an approximation of the Pareto Front representing optimal tradeoffs for IMRT plans. Prognostic information from the dosimetrics of the plans, and from patient-specific clinical variables were combined by the influence diagram. QALEs were calculated for each plan for each set of patient characteristics. Sensitivity analyses were conducted to explore changes in outcomes for variations in patient characteristics and dosimetric variables. The model calculated life expectancies that were in agreement with an independent clinical study. The radiation therapy model proposed has integrated a number of different physical, biological and clinical models into a more comprehensive model. It illustrates a number of the critical aspects of treatment planning that can be improved and represents a more detailed description of the therapy process. A Markov model was implemented to provide a stronger connection between dosimetric variables and clinical outcomes and could provide a practical, quantitative method for making difficult clinical decisions.

State fusion entropy for continuous and site-specific analysis of landslide stability changing regularities

NASA Astrophysics Data System (ADS)

Liu, Yong; Qin, Zhimeng; Hu, Baodan; Feng, Shuai

2018-04-01

Stability analysis is of great significance to landslide hazard prevention, especially the dynamic stability. However, many existing stability analysis methods are difficult to analyse the continuous landslide stability and its changing regularities in a uniform criterion due to the unique landslide geological conditions. Based on the relationship between displacement monitoring data, deformation states and landslide stability, a state fusion entropy method is herein proposed to derive landslide instability through a comprehensive multi-attribute entropy analysis of deformation states, which are defined by a proposed joint clustering method combining K-means and a cloud model. Taking Xintan landslide as the detailed case study, cumulative state fusion entropy presents an obvious increasing trend after the landslide entered accelerative deformation stage and historical maxima match highly with landslide macroscopic deformation behaviours in key time nodes. Reasonable results are also obtained in its application to several other landslides in the Three Gorges Reservoir in China. Combined with field survey, state fusion entropy may serve for assessing landslide stability and judging landslide evolutionary stages.

Automatic Dance Lesson Generation

ERIC Educational Resources Information Center

Yang, Yang; Leung, H.; Yue, Lihua; Deng, LiQun

2012-01-01

In this paper, an automatic lesson generation system is presented which is suitable in a learning-by-mimicking scenario where the learning objects can be represented as multiattribute time series data. The dance is used as an example in this paper to illustrate the idea. Given a dance motion sequence as the input, the proposed lesson generation…

Attributions for School Achievement of Anglo and Native American Community College Students.

ERIC Educational Resources Information Center

Powers, Stephen; Rossman, Mark H.

Attributions for school success and failure were examined among 211 community college students (112 Native Americans and 99 Anglos) enrolled in remedial reading classes at a large, urban multi-campus community college system in the Southwest. The Multidimensional-Multiattributional Causality Scale (MMCS) was administered to the students in their…

A Multiattributes Approach for Ranking PhD Programs

ERIC Educational Resources Information Center

Urbancic, Frank R.

2008-01-01

In its plan to combat the PhD shortage crisis, the Association to Advance Collegiate Schools of Business International (AACSB; 2003) has called for the development of PhD program rankings to serve as incentives for academic institutions to invest more in PhD programs, thereby counterbalancing the disproportionate influence of master of business…

Multi-attribute Regret-Based Dynamic Pricing

NASA Astrophysics Data System (ADS)

Jumadinova, Janyl; Dasgupta, Prithviraj

In this paper, we consider the problem of dynamic pricing by a set of competing sellers in an information economy where buyers differentiate products along multiple attributes, and buyer preferences can change temporally. Previous research in this area has either focused on dynamic pricing along a limited number of (e.g. binary) attributes, or, assumes that each seller has access to private information such as preference distribution of buyers, and profit/price information of other sellers. However, in real information markets, private information about buyers and sellers cannot be assumed to be available a priori. Moreover, due to the competition between sellers, each seller faces a tradeoff between accuracy and rapidity of the pricing mechanism. In this paper, we describe a multi-attribute dynamic pricing algorithm based on minimax regret that can be used by a seller's agent called a pricebot, to maximize the seller's utility. Our simulation results show that the minimax regret based dynamic pricing algorithm performs significantly better than other algorithms for rapidly and dynamically tracking consumer attributes without using any private information from either buyers or sellers.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

A colored petri nets based workload evaluation model and its validation through Multi-Attribute Task Battery-II.

PubMed

Wang, Peng; Fang, Weining; Guo, Beiyuan

2017-04-01

This paper proposed a colored petri nets based workload evaluation model. A formal interpretation of workload was firstly introduced based on the process that reflection of petri nets components to task. A petri net based description of Multiple Resources theory was given by comprehending it from a new angle. A new application of VACP rating scales named V/A-C-P unit, and the definition of colored transitions were proposed to build a model of task process. The calculation of workload mainly has the following four steps: determine token's initial position and values; calculate the weight of directed arcs on the basis of the rules proposed; calculate workload from different transitions, and correct the influence of repetitive behaviors. Verify experiments were carried out based on Multi-Attribute Task Battery-II software. Our results show that there is a strong correlation between the model values and NASA -Task Load Index scores (r=0.9513). In addition, this method can also distinguish behavior characteristics between different people. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

NASA Technical Reports Server (NTRS)

Patrick, Nicholas J. M.; Sheridan, Thomas B.

1996-01-01

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance vary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are: (1) determining what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major u.s. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort-topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimality with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider unmodelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

NASA Technical Reports Server (NTRS)

Patrick, Nicholas J. M.; Sheridan, Thomas B.

1996-01-01

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance x,ary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are (1) determining, what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major U.S. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimility with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider un-modelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Does the choice of tariff matter?

PubMed Central

Zhao, Yue; Li, Shun-Ping; Liu, Liu; Zhang, Jiang-Lin; Chen, Gang

2017-01-01

Abstract There is an increasing trend globally to develop country-specific tariffs that can theoretically better reflect population's preferences on health states for preference-based health-related quality-of-life instruments, also known as multiattribute utility instruments. This study focused on the most recently developed 5-level version of EuroQol-5 Dimension (EQ-5D) questionnaire, 1 of the world's most well-known multiattribute utility instruments, and aimed to empirically explore the agreements and known-group validities of applying the country-specific tariff versus tariffs developed from other countries using a sample of psoriasis vulgaris patients in Mainland China. A convenience sampling framework was adopted to recruit patients diagnosed with psoriasis vulgaris from Xiangya Hospital, Central South University, China, between May 2014 and February 2015. The 5-level EuroQol-5 dimensions (EQ-5D-5L) utilities were scored by using the Chinese, Japanese, and UK tariffs. Health state utilities were compared using a range of nonparametric test. The intraclass correlation coefficients and Bland–Altman plots were used to examine the agreements among the 3 EQ-5D-5L scores. Health state utility decrements between known groups were investigated using both effect size and a regression analysis. In all, 350 patients (aged 16 years or older) were recruited. There were significant differences among the 3 national tariff sets. Overall, 3 tariffs showed excellent agreements (intraclass correlation coefficient >0.90); however, the wide limits of agreement from the Bland–Altman plots suggest that these tariffs cannot be used interchangeably. The EQ-5D-5L scores using the Chinese-specific tariff showed the best known-group validity than the other 2 tariffs in this Chinese patient sample. The evidence from this study supports the choice of the country-specific tariff to be used in Mainland China. PMID:28834893

Construction of social value or utility-based health indices: the usefulness of factorial experimental design plans.

PubMed

Cadman, D; Goldsmith, C

1986-01-01

Global indices, which aggregate multiple health or function attributes into a single summary indicator, are useful measures in health research. Two key issues must be addressed in the initial stages of index construction from the universe of possible health and function attributes, which ones should be included in a new index? and how simple can the statistical model be to combine attributes into a single numeric index value? Factorial experimental designs were used in the initial stages of developing a function index for evaluating a program for the care of young handicapped children. Beginning with eight attributes judged important to the goals of the program by clinicians, social preference values for different function states were obtained from 32 parents of handicapped children and 32 members of the community. Using category rating methods each rater scored 16 written multi-attribute case descriptions which contained information about a child's status for all eight attributes. Either a good or poor level of each function attribute and age 3 or 5 years were described in each case. Thus, 2(8) = 256 different cases were rated. Two factorial design plans were selected and used to allocate case descriptions to raters. Analysis of variance determined that seven of the eight clinician selected attributes were required in a social value based index for handicapped children. Most importantly, the subsequent steps of index construction could be greatly simplified by the finding that a simple additive statistical model without complex attribute interaction terms was adequate for the index. We conclude that factorial experimental designs are an efficient, feasible and powerful tool for the initial stages of constructing a multi-attribute health index.

Using Multiattribute Utility Copulas in Support of UAV Search and Destroy Operations

DTIC Science & Technology

2012-03-01

1, ..., n. (2.3) where ai = a(1 − li) and bi = 1 − ai = ali + b. This implies the same mathe- matical properties of a strictly increasing cumulative...and DTMC defined target movement. Abdelhafiz et al. [6] present several instances of the multi-objective UAV mis- sion planning problem where the

Putting Short-Term Memory into Context: Reply to Usher, Davelaar, Haarmann, and Goshen-Gottstein (2008)

ERIC Educational Resources Information Center

Kahana, Michael J.; Sederberg, Per B.; Howard, Marc W.

2008-01-01

The temporal context model posits that search through episodic memory is driven by associations between the multiattribute representations of items and context. Context, in turn, is a recency weighted sum of previous experiences or memories. Because recently processed items are most similar to the current representation of context, M. Usher, E. J.…

A pseudo-sequential choice model for valuing multi-attribute environmental policies or programs in contingent valuation applications

Treesearch

Dmitriy Volinskiy; John C Bergstrom; Christopher M Cornwell; Thomas P Holmes

2010-01-01

The assumption of independence of irrelevant alternatives in a sequential contingent valuation format should be questioned. Statistically, most valuation studies treat nonindependence as a consequence of unobserved individual effects. Another approach is to consider an inferential process in which any particular choice is part of a general choosing strategy of a survey...

Gender Differences in Multiattributional Causality for Achievement and Affiliation in Five Cross-National Samples.

ERIC Educational Resources Information Center

Chandler, Theodore A.; And Others

The purpose of this study was to expand the previous limited locus of control focus of gender differences cross-nationally by shifting to an attributional model for both successes and failures in both achievement and affiliation domains in order to test the hypothesis that women differ from men in their attributional patterns for achievement and…

Enhancing Collaborative Peer-to-Peer Systems Using Resource Aggregation and Caching: A Multi-Attribute Resource and Query Aware Approach

ERIC Educational Resources Information Center

Bandara, H. M. N. Dilum

2012-01-01

Resource-rich computing devices, decreasing communication costs, and Web 2.0 technologies are fundamentally changing the way distributed applications communicate and collaborate. With these changes, we envision Peer-to-Peer (P2P) systems that will allow for the integration and collaboration of peers with diverse capabilities to a virtual community…

Prioritizing conservation seed banking locations for imperiled hemlock species using multi-attribute frontier mapping

Treesearch

John M. Hastings; Kevin M. Potter; Frank H. Koch; Mark Megalos; Robert M. Jetton

2017-01-01

Hemlock woolly adelgid (Adelges tsugae Annand) (HWA) is an invasive forest insect sweeping across the native range of eastern (Tsuga canadensis [L.] Carr.) and Carolina (Tsuga caroliniana Engelm.) hemlocks, threatening to severely reduce eastern hemlock extent and to push Carolina hemlock to extirpation. HWA poses a significant threat to these eastern US natives, now...

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

Detecting Hotspot Information Using Multi-Attribute Based Topic Model

PubMed Central

Wang, Jing; Li, Li; Tan, Feng; Zhu, Ying; Feng, Weisi

2015-01-01

Microblogging as a kind of social network has become more and more important in our daily lives. Enormous amounts of information are produced and shared on a daily basis. Detecting hot topics in the mountains of information can help people get to the essential information more quickly. However, due to short and sparse features, a large number of meaningless tweets and other characteristics of microblogs, traditional topic detection methods are often ineffective in detecting hot topics. In this paper, we propose a new topic model named multi-attribute latent dirichlet allocation (MA-LDA), in which the time and hashtag attributes of microblogs are incorporated into LDA model. By introducing time attribute, MA-LDA model can decide whether a word should appear in hot topics or not. Meanwhile, compared with the traditional LDA model, applying hashtag attribute in MA-LDA model gives the core words an artificially high ranking in results meaning the expressiveness of outcomes can be improved. Empirical evaluations on real data sets demonstrate that our method is able to detect hot topics more accurately and efficiently compared with several baselines. Our method provides strong evidence of the importance of the temporal factor in extracting hot topics. PMID:26496635

A View on the Importance of "Multi-Attribute Method" for Measuring Purity of Biopharmaceuticals and Improving Overall Control Strategy.

PubMed

Rogers, Richard S; Abernathy, Michael; Richardson, Douglas D; Rouse, Jason C; Sperry, Justin B; Swann, Patrick; Wypych, Jette; Yu, Christopher; Zang, Li; Deshpande, Rohini

2017-11-30

Today, we are experiencing unprecedented growth and innovation within the pharmaceutical industry. Established protein therapeutic modalities, such as recombinant human proteins, monoclonal antibodies (mAbs), and fusion proteins, are being used to treat previously unmet medical needs. Novel therapies such as bispecific T cell engagers (BiTEs), chimeric antigen T cell receptors (CARTs), siRNA, and gene therapies are paving the path towards increasingly personalized medicine. This advancement of new indications and therapeutic modalities is paralleled by development of new analytical technologies and methods that provide enhanced information content in a more efficient manner. Recently, a liquid chromatography-mass spectrometry (LC-MS) multi-attribute method (MAM) has been developed and designed for improved simultaneous detection, identification, quantitation, and quality control (monitoring) of molecular attributes (Rogers et al. MAbs 7(5):881-90, 2015). Based on peptide mapping principles, this powerful tool represents a true advancement in testing methodology that can be utilized not only during product characterization, formulation development, stability testing, and development of the manufacturing process, but also as a platform quality control method in dispositioning clinical materials for both innovative biotherapeutics and biosimilars.

Stimulus Value Signals in Ventromedial PFC Reflect the Integration of Attribute Value Signals Computed in Fusiform Gyrus and Posterior Superior Temporal Gyrus

PubMed Central

Lim, Seung-Lark; O'Doherty, John P.

2013-01-01

We often have to make choices among multiattribute stimuli (e.g., a food that differs on its taste and health). Behavioral data suggest that choices are made by computing the value of the different attributes and then integrating them into an overall stimulus value signal. However, it is not known whether this theory describes the way the brain computes the stimulus value signals, or how the underlying computations might be implemented. We investigated these questions using a human fMRI task in which individuals had to evaluate T-shirts that varied in their visual esthetic (e.g., color) and semantic (e.g., meaning of logo printed in T-shirt) components. We found that activity in the fusiform gyrus, an area associated with the processing of visual features, correlated with the value of the visual esthetic attributes, but not with the value of the semantic attributes. In contrast, activity in posterior superior temporal gyrus, an area associated with the processing of semantic meaning, exhibited the opposite pattern. Furthermore, both areas exhibited functional connectivity with an area of ventromedial prefrontal cortex that reflects the computation of overall stimulus values at the time of decision. The results provide supporting evidence for the hypothesis that some attribute values are computed in cortical areas specialized in the processing of such features, and that those attribute-specific values are then passed to the vmPFC to be integrated into an overall stimulus value signal to guide the decision. PMID:23678116

Stimulus value signals in ventromedial PFC reflect the integration of attribute value signals computed in fusiform gyrus and posterior superior temporal gyrus.

PubMed

Lim, Seung-Lark; O'Doherty, John P; Rangel, Antonio

2013-05-15

We often have to make choices among multiattribute stimuli (e.g., a food that differs on its taste and health). Behavioral data suggest that choices are made by computing the value of the different attributes and then integrating them into an overall stimulus value signal. However, it is not known whether this theory describes the way the brain computes the stimulus value signals, or how the underlying computations might be implemented. We investigated these questions using a human fMRI task in which individuals had to evaluate T-shirts that varied in their visual esthetic (e.g., color) and semantic (e.g., meaning of logo printed in T-shirt) components. We found that activity in the fusiform gyrus, an area associated with the processing of visual features, correlated with the value of the visual esthetic attributes, but not with the value of the semantic attributes. In contrast, activity in posterior superior temporal gyrus, an area associated with the processing of semantic meaning, exhibited the opposite pattern. Furthermore, both areas exhibited functional connectivity with an area of ventromedial prefrontal cortex that reflects the computation of overall stimulus values at the time of decision. The results provide supporting evidence for the hypothesis that some attribute values are computed in cortical areas specialized in the processing of such features, and that those attribute-specific values are then passed to the vmPFC to be integrated into an overall stimulus value signal to guide the decision.

New Tools and Methods for Assessing Risk-Management Strategies

DTIC Science & Technology

2004-03-01

Theories to evaluate the risks and benefits of various acquisition alternatives and allowed researchers to monitor the process students used to make a...revealed distinct risk-management strategies. 15. SUBJECT TERMS risk managements, acquisition process, expected value theory , multi-attribute utility theory ...Utility Theories to evaluate the risks and benefits of various acquisition alternatives, and allowed us to monitor the process subjects used to arrive at

Assessing land clearing potential in the Canadian agriculture–forestry interface with a multi-attribute frontier approach

Treesearch

Denys Yemshanov; Frank Koch; Kurt H. Riitters; Brian McConkey; Ted Huffmand; Stephen Smithe

2015-01-01

The pattern of forest land clearing in a region can be viewed as a gauge of sustainable (or unsustain-able) use of agricultural and forest resources. In this study we examine the geographical distribution ofland clearing potential in the Canadian agriculture–forestry interface and propose a new landscape-scaleindicator that quantifies this potential. We consider the...

Using Incentives to Align Individual Choice with Organiztional Objectives

DTIC Science & Technology

2009-10-01

International Personality Item Pool – facet level items - Subject pool » University Students – 1st generation college – 18-24 years old, smaller sample 30... Services , Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be...organizational objectives • 4 sets of experiments - Multi-attribute Auction » Precursor to Assignment Incentive Pay (AIP) - Cafeteria Style

A Multi-Attribute Assessment of Site Preparation Effects on the Socioeconomical and Ecological Attributes of Loblolly Pine (Pinus taeda) Stands

Treesearch

James H. Miller; Jianbang Gan; Stephen H. Kolison; Robert S. Boyd; Kenneth L. McNabb; B. Graeme Lockaby

1998-01-01

The public demands both commodity and non-commodity goods and srvices from our forests. This requires management options that not only provide fiber, clean water, wildlife habitat, and mcreation, but do so in a biologically sustainable manner, resulting in healthy productive forests into perpetuity. A common forest management activity used to enhance fiber production...

Mapping Fire Severity Using Imaging Spectroscopy and Kernel Based Image Analysis

NASA Astrophysics Data System (ADS)

Prasad, S.; Cui, M.; Zhang, Y.; Veraverbeke, S.

2014-12-01

Improved spatial representation of within-burn heterogeneity after wildfires is paramount to effective land management decisions and more accurate fire emissions estimates. In this work, we demonstrate feasibility and efficacy of airborne imaging spectroscopy (hyperspectral imagery) for quantifying wildfire burn severity, using kernel based image analysis techniques. Two different airborne hyperspectral datasets, acquired over the 2011 Canyon and 2013 Rim fire in California using the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) sensor, were used in this study. The Rim Fire, covering parts of the Yosemite National Park started on August 17, 2013, and was the third largest fire in California's history. Canyon Fire occurred in the Tehachapi mountains, and started on September 4, 2011. In addition to post-fire data for both fires, half of the Rim fire was also covered with pre-fire images. Fire severity was measured in the field using Geo Composite Burn Index (GeoCBI). The field data was utilized to train and validate our models, wherein the trained models, in conjunction with imaging spectroscopy data were used for GeoCBI estimation wide geographical regions. This work presents an approach for using remotely sensed imagery combined with GeoCBI field data to map fire scars based on a non-linear (kernel based) epsilon-Support Vector Regression (e-SVR), which was used to learn the relationship between spectra and GeoCBI in a kernel-induced feature space. Classification of healthy vegetation versus fire-affected areas based on morphological multi-attribute profiles was also studied. The availability of pre- and post-fire imaging spectroscopy data over the Rim Fire provided a unique opportunity to evaluate the performance of bi-temporal imaging spectroscopy for assessing post-fire effects. This type of data is currently constrained because of limited airborne acquisitions before a fire, but will become widespread with future spaceborne sensors such as those on the planned NASA HyspIRI mission.

Multiple imputation to deal with missing EQ-5D-3L data: Should we impute individual domains or the actual index?

PubMed

Simons, Claire L; Rivero-Arias, Oliver; Yu, Ly-Mee; Simon, Judit

2015-04-01

Missing data are a well-known and widely documented problem in cost-effectiveness analyses alongside clinical trials using individual patient-level data. Current methodological research recommends multiple imputation (MI) to deal with missing health outcome data, but there is little guidance on whether MI for multi-attribute questionnaires, such as the EQ-5D-3L, should be carried out at domain or at summary score level. In this paper, we evaluated the impact of imputing individual domains versus imputing index values to deal with missing EQ-5D-3L data using a simulation study and developed recommendations for future practice. We simulated missing data in a patient-level dataset with complete EQ-5D-3L data at one point in time from a large multinational clinical trial (n = 1,814). Different proportions of missing data were generated using a missing at random (MAR) mechanism and three different scenarios were studied. The performance of using each method was evaluated using root mean squared error and mean absolute error of the actual versus predicted EQ-5D-3L indices. In large sample sizes (n > 500) and a missing data pattern that follows mainly unit non-response, imputing domains or the index produced similar results. However, domain imputation became more accurate than index imputation with pattern of missingness following an item non-response. For smaller sample sizes (n < 100), index imputation was more accurate. When MI models were misspecified, both domain and index imputations were inaccurate for any proportion of missing data. The decision between imputing the domains or the EQ-5D-3L index scores depends on the observed missing data pattern and the sample size available for analysis. Analysts conducting this type of exercises should also evaluate the sensitivity of the analysis to the MAR assumption and whether the imputation model is correctly specified.

MANCaLog: A Logic for Multi-Attribute Network Cascades

DTIC Science & Technology

2013-01-01

influence function , whose precise effects will be described later on when we discuss the semantics. As a result, a rule consists of four major parts...i) an influence function , (ii) neighbor criteria, (iii) target criteria, and (iv) a target. Intuitively, (i) specifies how the neighbors influence the...in terms of these elements. First, we define influence functions and neighbor criteria. Definition 2.6 ( Influence Function ). An influence function is a

Multiattribute Fixed-State Utility Assessment.

DTIC Science & Technology

1981-03-27

of a companion distribution, are presented in Appendix A. Because of the theory of conditional expected utility and the modelling of the utilities by...obtain approximations to the moments, using the companion V ) ) distribution discussed in Section 3. The moments of both distributions are discussed...1956b, 21, 207-216. Slavic, P. "From Shakespeare to Simon: Speculation -- and some evidence -- about man’s ability to process information." O g . a

Bidding Behavior in a Multi-attribute First-price Auction

DTIC Science & Technology

2010-01-01

of applying key features of the multi-unit auction to proxy buyer /seller marginal valuations of the attributes of a job. Two experiments were...compensation package show promise in ascertaining buyer /seller marginal valuations of a job. This research effort was supported by a grant from the...auctions observed in the goods market, as measured by maximizing consumer and producer surplus, are likely to have promising applications to labor markets

An Interactive Computer Program for Assessing and Using Multiattribute Utility Functions

DTIC Science & Technology

1975-06-01

involved evaluating five options for dealing with the question of legalizing prostitution in the Boston area. These options were strict prohibition...MUFCAP Has 69 Been Applied 5.4.1 Evaluating Health Plans 69 5.4.2 Evaluating Policies for Dealing with 69 Prostitution in the Boston...toleration or benign neglect, regula- tion of prostitution , licensing of individual prostitutes and decriminalization. The attributes ware chosen to

Does the choice of tariff matter?: A comparison of EQ-5D-5L utility scores using Chinese, UK, and Japanese tariffs on patients with psoriasis vulgaris in Central South China.

PubMed

Zhao, Yue; Li, Shun-Ping; Liu, Liu; Zhang, Jiang-Lin; Chen, Gang

2017-08-01

There is an increasing trend globally to develop country-specific tariffs that can theoretically better reflect population's preferences on health states for preference-based health-related quality-of-life instruments, also known as multiattribute utility instruments. This study focused on the most recently developed 5-level version of EuroQol-5 Dimension (EQ-5D) questionnaire, 1 of the world's most well-known multiattribute utility instruments, and aimed to empirically explore the agreements and known-group validities of applying the country-specific tariff versus tariffs developed from other countries using a sample of psoriasis vulgaris patients in Mainland China.A convenience sampling framework was adopted to recruit patients diagnosed with psoriasis vulgaris from Xiangya Hospital, Central South University, China, between May 2014 and February 2015. The 5-level EuroQol-5 dimensions (EQ-5D-5L) utilities were scored by using the Chinese, Japanese, and UK tariffs. Health state utilities were compared using a range of nonparametric test. The intraclass correlation coefficients and Bland-Altman plots were used to examine the agreements among the 3 EQ-5D-5L scores. Health state utility decrements between known groups were investigated using both effect size and a regression analysis.In all, 350 patients (aged 16 years or older) were recruited. There were significant differences among the 3 national tariff sets. Overall, 3 tariffs showed excellent agreements (intraclass correlation coefficient >0.90); however, the wide limits of agreement from the Bland-Altman plots suggest that these tariffs cannot be used interchangeably. The EQ-5D-5L scores using the Chinese-specific tariff showed the best known-group validity than the other 2 tariffs in this Chinese patient sample. The evidence from this study supports the choice of the country-specific tariff to be used in Mainland China.

Parameter Validation for Evaluation of Spaceflight Hardware Reusability

NASA Technical Reports Server (NTRS)

Childress-Thompson, Rhonda; Dale, Thomas L.; Farrington, Phillip

2017-01-01

Within recent years, there has been an influx of companies around the world pursuing reusable systems for space flight. Much like NASA, many of these new entrants are learning that reusable systems are complex and difficult to acheive. For instance, in its first attempts to retrieve spaceflight hardware for future reuse, SpaceX unsuccessfully tried to land on a barge at sea, resulting in a crash-landing. As this new generation of launch developers continues to develop concepts for reusable systems, having a systematic approach for determining the most effective systems for reuse is paramount. Three factors that influence the effective implementation of reusability are cost, operability and reliability. Therefore, a method that integrates these factors into the decision-making process must be utilized to adequately determine whether hardware used in space flight should be reused or discarded. Previous research has identified seven features that contribute to the successful implementation of reusability for space flight applications, defined reusability for space flight applications, highlighted the importance of reusability, and presented areas that hinder successful implementation of reusability. The next step is to ensure that the list of reusability parameters previously identified is comprehensive, and any duplication is either removed or consolidated. The characteristics to judge the seven features as good indicators for successful reuse are identified and then assessed using multiattribute decision making. Next, discriminators in the form of metrics or descriptors are assigned to each parameter. This paper explains the approach used to evaluate these parameters, define the Measures of Effectiveness (MOE) for reusability, and quantify these parameters. Using the MOEs, each parameter is assessed for its contribution to the reusability of the hardware. Potential data sources needed to validate the approach will be identified.

Multi-attribute criteria applied to electric generation energy system analysis LDRD.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuswa, Glenn W.; Tsao, Jeffrey Yeenien; Drennen, Thomas E.

2005-10-01

This report began with a Laboratory-Directed Research and Development (LDRD) project to improve Sandia National Laboratories multidisciplinary capabilities in energy systems analysis. The aim is to understand how various electricity generating options can best serve needs in the United States. The initial product is documented in a series of white papers that span a broad range of topics, including the successes and failures of past modeling studies, sustainability, oil dependence, energy security, and nuclear power. Summaries of these projects are included here. These projects have provided a background and discussion framework for the Energy Systems Analysis LDRD team to carrymore » out an inter-comparison of many of the commonly available electric power sources in present use, comparisons of those options, and efforts needed to realize progress towards those options. A computer aid has been developed to compare various options based on cost and other attributes such as technological, social, and policy constraints. The Energy Systems Analysis team has developed a multi-criteria framework that will allow comparison of energy options with a set of metrics that can be used across all technologies. This report discusses several evaluation techniques and introduces the set of criteria developed for this LDRD.« less

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

NASA Technical Reports Server (NTRS)

Siapkaras, A.

1977-01-01

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

Pros and cons of conjoint analysis of discrete choice experiments to define classification and response criteria in rheumatology.

PubMed

Taylor, William J

2016-03-01

Conjoint analysis of choice or preference data has been used in marketing for over 40 years but has appeared in healthcare settings much more recently. It may be a useful technique for applications within the rheumatology field. Conjoint analysis in rheumatology contexts has mainly used the approaches implemented in 1000Minds Ltd, Dunedin, New Zealand, Sawtooth Software, Orem UT, USA. Examples include classification criteria, composite response criteria, service prioritization tools and utilities assessment. Limitations imposed by very many attributes can be managed using new techniques. Conjoint analysis studies of classification and response criteria suggest that the assumption of equal weighting of attributes cannot be met, which challenges traditional approaches to composite criteria construction. Weights elicited through choice experiments with experts can derive more accurate classification criteria, than unweighted criteria. Studies that find significant variation in attribute weights for composite response criteria for gout make construction of such criteria problematic. Better understanding of various multiattribute phenomena is likely to increase with increased use of conjoint analysis, especially when the attributes concern individual perceptions or opinions. In addition to classification criteria, some applications for conjoint analysis that are emerging in rheumatology include prioritization tools, remission criteria, and utilities for life areas.

An Index of Trauma Severity Based on Multiattribute Utility: An Illustration of Complex Utility Modeling.

DTIC Science & Technology

1981-10-01

measure for Central Nervus System is the Glasgow Cons Score (GCS), a scale of brain and spinal cord injury (Langfitt [1978]), and is itself an additive...concerns directly relating to the injury itself were identified. These were: 1. Ventilation Severity 2 Circulation Severity 3. Central Nervous System ...interacting system within which these concerns represent interacting parts. Most trauma involves only one of these systems , but more than one may be

Selection of an Optimum Air Defense Weapon Package Using MAUM (Multi-Attribute Utility Measurement).

DTIC Science & Technology

1983-06-01

SELECTION OF AN OPTIMUM AIR DEFENSE WEAPON PACKAGE USING MAUM by Wilton L. Ham June 1983 Thesis Advisor: R. G. Nickerson Approved for public release...OSSTRIUTON STATEMEN4T (of if AlRpeat) Approved for public release; distribution unlimited. I?. 01STVAGUTgOg STATE[MENT (of me ubeh’ei antered Ian...hold": do not fire except in self defense. 4. Firing Commands. These are commands issued regard- less of the weapons control in effect. There are three

Development of a multi-criteria evaluation system to assess growing pig welfare.

PubMed

Martín, P; Traulsen, I; Buxadé, C; Krieter, J

2017-03-01

The aim of this paper was to present an alternative multi-criteria evaluation model to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. The WQ assessment protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first step of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion. The utility functions and the aggregation function were constructed in two separated steps. The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) method was used for utility function determination and the Choquet Integral (CI) was used as an aggregation operator. The WQ decision-makers' preferences were fitted in order to construct the utility functions and to determine the CI parameters. The methods were tested with generated data sets for farms of growing pigs. Using the MAUT, similar results were obtained to the ones obtained applying the WQ protocol aggregation methods. It can be concluded that due to the use of an interactive approach such as MACBETH, this alternative methodology is more transparent and more flexible than the methodology proposed by WQ, which allows the possibility to modify the model according, for instance, to new scientific knowledge.

A unifying Bayesian account of contextual effects in value-based choice

PubMed Central

Friston, Karl J.; Dolan, Raymond J.

2017-01-01

Empirical evidence suggests the incentive value of an option is affected by other options available during choice and by options presented in the past. These contextual effects are hard to reconcile with classical theories and have inspired accounts where contextual influences play a crucial role. However, each account only addresses one or the other of the empirical findings and a unifying perspective has been elusive. Here, we offer a unifying theory of context effects on incentive value attribution and choice based on normative Bayesian principles. This formulation assumes that incentive value corresponds to a precision-weighted prediction error, where predictions are based upon expectations about reward. We show that this scheme explains a wide range of contextual effects, such as those elicited by other options available during choice (or within-choice context effects). These include both conditions in which choice requires an integration of multiple attributes and conditions where a multi-attribute integration is not necessary. Moreover, the same scheme explains context effects elicited by options presented in the past or between-choice context effects. Our formulation encompasses a wide range of contextual influences (comprising both within- and between-choice effects) by calling on Bayesian principles, without invoking ad-hoc assumptions. This helps clarify the contextual nature of incentive value and choice behaviour and may offer insights into psychopathologies characterized by dysfunctional decision-making, such as addiction and pathological gambling. PMID:28981514

Effects on Environmental and Socioeconomic Sustainability of Producing Ethanol from Perennial Grasses

NASA Astrophysics Data System (ADS)

Dale, V. H.; Parish, E. S.

2016-12-01

Using perennial grasses to produce ethanol can enhance progress toward sustainability. A suite of 35 environmental and socioeconomic sustainability indicators was considered in a holistic sustainability assessment of a five-year switchgrass-to-ethanol production experiment centered on a demonstration-scale biorefinery in Vonore, Tennessee. By combining field measurements, literature review and expert opinion, the team was able to rate 28 of the 35 recommended sustainability indicators. The team combined these ratings within a multi-attribute decision support system tool and used this information to compare the sustainability of producing 2118 hectares of no-till switchgrass relative to two alternative business-as-usual scenarios of unmanaged pasture and tilled corn production. The results suggest that East Tennessee switchgrass production improves environmental quality overall and can be beneficial to the counties surrounding the biorefinery in terms of dollars earned and jobs created. The timing of switchgrass production also provides an opportunity to use inactive equipment and laborers. By incorporating a landscape design approach, the opportunities, constraints and most reasonable paths forward for growing bioenergy feedstock in specific context can be assessed in a way that adapts and improves local practices. Lessons learned from this case study are being incorporated into sustainability assessments of corn stover in Iowa and a variety of bioenergy feedstocks in diverse settings. The overall goal is to develop sound management practices that can address the multiple and sometimes competing demands of stakeholders.

Mapping between 6 Multiattribute Utility Instruments.

PubMed

Chen, Gang; Khan, Munir A; Iezzi, Angelo; Ratcliffe, Julie; Richardson, Jeff

2016-02-01

Cost-utility analyses commonly employ a multiattribute utility (MAU) instrument to estimate the health state utilities, which are needed to calculate quality-adjusted life years. Different MAU instruments predict significantly different utilities, which makes comparison of results from different evaluation studies problematical. This article presents mapping functions ("crosswalks") from 6 MAU instruments (EQ-5D-5L, SF-6D, Health Utilities Index 3 [HUI 3], 15D, Quality of Well-Being [QWB], and Assessment of Quality of Life 8D [AQoL-8D]) to each of the other 5 instruments in the study: a total of 30 mapping functions. Data were obtained from a multi-instrument comparison survey of the public and patients in 7 disease areas conducted in 6 countries (Australia, Canada, Germany, Norway, United Kingdom, and United States). The 8022 respondents were administered each of the 6 study instruments. Mapping equations between each instrument pair were estimated using 4 econometric techniques: ordinary least squares, generalized linear model, censored least absolute deviations, and, for the first time, a robust MM-estimator. Goodness-of-fit indicators for each of the results are within the range of published studies. Transformations reduced discrepancies between predicted utilities. Incremental utilities, which determine the value of quality-related health benefits, are almost perfectly aligned at the sample means. Transformations presented here align the measurement scales of MAU instruments. Their use will increase confidence in the comparability of evaluation studies, which have employed different MAU instruments. © The Author(s) 2015.

A Literature Review and Compilation of Nuclear Waste Management System Attributes for Use in Multi-Objective System Evaluations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalinina, Elena Arkadievna; Samsa, Michael

The purpose of this work was to compile a comprehensive initial set of potential nuclear waste management system attributes. This initial set of attributes is intended to serve as a starting point for additional consideration by system analysts and planners to facilitate the development of a waste management system multi-objective evaluation framework based on the principles and methodology of multi-attribute utility analysis. The compilation is primarily based on a review of reports issued by the Canadian Nuclear Waste Management Organization (NWMO) and the Blue Ribbon Commission on America's Nuclear Future (BRC), but also an extensive review of the available literaturemore » for similar and past efforts as well. Numerous system attributes found in different sources were combined into a single objectives-oriented hierarchical structure. This study provides a discussion of the data sources and the descriptions of the hierarchical structure. A particular focus of this study was on collecting and compiling inputs from past studies that involved the participation of various external stakeholders. However, while the important role of stakeholder input in a country's waste management decision process is recognized in the referenced sources, there are only a limited number of in-depth studies of the stakeholders' differing perspectives. Compiling a comprehensive hierarchical listing of attributes is a complex task since stakeholders have multiple and often conflicting interests. The BRC worked for two years (January 2010 to January 2012) to "ensure it has heard from as many points of view as possible." The Canadian NWMO study took four years and ample resources, involving national and regional stakeholders' dialogs, internet-based dialogs, information and discussion sessions, open houses, workshops, round tables, public attitude research, website, and topic reports. The current compilation effort benefited from the distillation of these many varied inputs conducted by the previous studies.« less

Optimisation study of a vehicle bumper subsystem with fuzzy parameters

NASA Astrophysics Data System (ADS)

Farkas, L.; Moens, D.; Donders, S.; Vandepitte, D.

2012-10-01

This paper deals with the design and optimisation for crashworthiness of a vehicle bumper subsystem, which is a key scenario for vehicle component design. The automotive manufacturers and suppliers have to find optimal design solutions for such subsystems that comply with the conflicting requirements of the regulatory bodies regarding functional performance (safety and repairability) and regarding the environmental impact (mass). For the bumper design challenge, an integrated methodology for multi-attribute design engineering of mechanical structures is set up. The integrated process captures the various tasks that are usually performed manually, this way facilitating the automated design iterations for optimisation. Subsequently, an optimisation process is applied that takes the effect of parametric uncertainties into account, such that the system level of failure possibility is acceptable. This optimisation process is referred to as possibility-based design optimisation and integrates the fuzzy FE analysis applied for the uncertainty treatment in crash simulations. This process is the counterpart of the reliability-based design optimisation used in a probabilistic context with statistically defined parameters (variabilities).

Neural network analysis of crosshole tomographic images: The seismic signature of gas hydrate bearing sediments in the Mackenzie Delta (NW Canada)

NASA Astrophysics Data System (ADS)

Bauer, K.; Pratt, R. G.; Haberland, C.; Weber, M.

2008-10-01

Crosshole seismic experiments were conducted to study the in-situ properties of gas hydrate bearing sediments (GHBS) in the Mackenzie Delta (NW Canada). Seismic tomography provided images of P velocity, anisotropy, and attenuation. Self-organizing maps (SOM) are powerful neural network techniques to classify and interpret multi-attribute data sets. The coincident tomographic images are translated to a set of data vectors in order to train a Kohonen layer. The total gradient of the model vectors is determined for the trained SOM and a watershed segmentation algorithm is used to visualize and map the lithological clusters with well-defined seismic signatures. Application to the Mallik data reveals four major litho-types: (1) GHBS, (2) sands, (3) shale/coal interlayering, and (4) silt. The signature of seismic P wave characteristics distinguished for the GHBS (high velocities, strong anisotropy and attenuation) is new and can be used for new exploration strategies to map and quantify gas hydrates.

DICON: interactive visual analysis of multidimensional clusters.

PubMed

Cao, Nan; Gotz, David; Sun, Jimeng; Qu, Huamin

2011-12-01

Clustering as a fundamental data analysis technique has been widely used in many analytic applications. However, it is often difficult for users to understand and evaluate multidimensional clustering results, especially the quality of clusters and their semantics. For large and complex data, high-level statistical information about the clusters is often needed for users to evaluate cluster quality while a detailed display of multidimensional attributes of the data is necessary to understand the meaning of clusters. In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information. We further develop a novel layout algorithm which can generate similar icons for similar clusters, making comparisons of clusters easier. User interaction and clutter reduction are integrated into the system to help users more effectively analyze and refine clustering results for large datasets. We demonstrate the power of DICON through a user study and a case study in the healthcare domain. Our evaluation shows the benefits of the technique, especially in support of complex multidimensional cluster analysis. © 2011 IEEE

Application of Visual Attention in Seismic Attribute Analysis

NASA Astrophysics Data System (ADS)

He, M.; Gu, H.; Wang, F.

2016-12-01

It has been proved that seismic attributes can be used to predict reservoir. The joint of multi-attribute and geological statistics, data mining, artificial intelligence, further promote the development of the seismic attribute analysis. However, the existing methods tend to have multiple solutions and insufficient generalization ability, which is mainly due to the complex relationship between seismic data and geological information, and undoubtedly own partly to the methods applied. Visual attention is a mechanism model of the human visual system which can concentrate on a few significant visual objects rapidly, even in a mixed scene. Actually, the model qualify good ability of target detection and recognition. In our study, the targets to be predicted are treated as visual objects, and an object representation based on well data is made in the attribute dimensions. Then in the same attribute space, the representation is served as a criterion to search the potential targets outside the wells. This method need not predict properties by building up a complicated relation between attributes and reservoir properties, but with reference to the standard determined before. So it has pretty good generalization ability, and the problem of multiple solutions can be weakened by defining the threshold of similarity.

DETERMINATION OF RELATIVE IMPORTANCE OF NONPROLIFERATION FACTORS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Richard Metcalf

2009-07-01

Methodologies to determine the proliferation resistance (PR) of nuclear facilities often rely on either expert elicitation, a resource-intensive approach without easily reproducible results, or numeric evaluations, which can fail to take into account the institutional knowledge and expert experience of the nonproliferation community. In an attempt to bridge the gap and bring the institutional knowledge into numeric evaluations of PR, a survey was conducted of 33 individuals to find the relative importance of a set of 62 nonproliferation factors, subsectioned into groups under the headings of Diversion, Transportation, Transformation, and Weaponization. One third of the respondents were self-described nonproliferation professionals,more » and the remaining two thirds were from secondary professions related to nonproliferation, such as industrial engineers or policy analysts. The factors were taken from previous work which used multi-attribute utility analysis with uniform weighting of attributes and did not include institutional knowledge. In both expert and non-expert groups, all four headings and the majority of factors had different relative importance at a confidence of 95% (p=0.05). This analysis and survey demonstrates that institutional knowledge can be brought into numeric evaluations of PR, if there is a sufficient investment of resources made prior to the evaluation.« less

Bridging the Gap: Need for a Data Repository to Support Vaccine Prioritization Efforts*

PubMed Central

Madhavan, Guruprasad; Phelps, Charles; Sangha, Kinpritma; Levin, Scott; Rappuoli, Rino

2015-01-01

As the mechanisms for discovery, development, and delivery of new vaccines become increasingly complex, strategic planning and priority setting have become ever more crucial. Traditional single value metrics such as disease burden or cost-effectiveness no longer suffice to rank vaccine candidates for development. The Institute of Medicine—in collaboration with the National Academy of Engineering—has developed a novel software system to support vaccine prioritization efforts. The Strategic Multi-Attribute Ranking Tool for Vaccines—SMART Vaccines—allows decision makers to specify their own value structure, selecting from among 28 pre-defined and up to 7 user-defined attributes relevant to the ranking of vaccine candidates. Widespread use of SMART Vaccines will require compilation of a comprehensive data repository for numerous relevant populations—including their demographics, disease burdens and associated treatment costs, as well as characterizing performance features of potential or existing vaccines that might be created, improved, or deployed. While the software contains preloaded data for a modest number of populations, a large gap exists between the existing data and a comprehensive data repository necessary to make full use of SMART Vaccines. While some of these data exist in disparate sources and forms, constructing a data repository will require much new coordination and focus. Finding strategies to bridge the gap to a comprehensive data repository remains the most important task in bringing SMART Vaccines to full fruition, and to support strategic vaccine prioritization efforts in general. PMID:26022565

A foundational methodology for determining system static complexity using notional lunar oxygen production processes

NASA Astrophysics Data System (ADS)

Long, Nicholas James

This thesis serves to develop a preliminary foundational methodology for evaluating the static complexity of future lunar oxygen production systems when extensive information is not yet available about the various systems under consideration. Evaluating static complexity, as part of a overall system complexity analysis, is an important consideration in ultimately selecting a process to be used in a lunar base. When system complexity is higher, there is generally an overall increase in risk which could impact the safety of astronauts and the economic performance of the mission. To evaluate static complexity in lunar oxygen production, static complexity is simplified and defined into its essential components. First, three essential dimensions of static complexity are investigated, including interconnective complexity, strength of connections, and complexity in variety. Then a set of methods is developed upon which to separately evaluate each dimension. Q-connectivity analysis is proposed as a means to evaluate interconnective complexity and strength of connections. The law of requisite variety originating from cybernetic theory is suggested to interpret complexity in variety. Secondly, a means to aggregate the results of each analysis is proposed to create holistic measurement for static complexity using the Single Multi-Attribute Ranking Technique (SMART). Each method of static complexity analysis and the aggregation technique is demonstrated using notional data for four lunar oxygen production processes.

Efficient bulk-loading of gridfiles

NASA Technical Reports Server (NTRS)

Leutenegger, Scott T.; Nicol, David M.

1994-01-01

This paper considers the problem of bulk-loading large data sets for the gridfile multiattribute indexing technique. We propose a rectilinear partitioning algorithm that heuristically seeks to minimize the size of the gridfile needed to ensure no bucket overflows. Empirical studies on both synthetic data sets and on data sets drawn from computational fluid dynamics applications demonstrate that our algorithm is very efficient, and is able to handle large data sets. In addition, we present an algorithm for bulk-loading data sets too large to fit in main memory. Utilizing a sort of the entire data set it creates a gridfile without incurring any overflows.

On the nature of bias and defects in the software specification process

NASA Technical Reports Server (NTRS)

Straub, Pablo A.; Zelkowitz, Marvin V.

1992-01-01

Implementation bias in a specification is an arbitrary constraint in the solution space. This paper describes the problem of bias. Additionally, this paper presents a model of the specification and design processes describing individual subprocesses in terms of precision/detail diagrams and a model of bias in multi-attribute software specifications. While studying how bias is introduced into a specification we realized that software defects and bias are dual problems of a single phenomenon. This was used to explain the large proportion of faults found during the coding phase at the Software Engineering Laboratory at NASA/GSFC.

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

Borne, K.; Becla, J.; Davidson, I.; Szalay, A.; Tyson, J. A.

2008-12-01

We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night) multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

The importance of environmental quality and catch potential to fishing site selection by freshwater anglers in Mississippi

USGS Publications Warehouse

Schramm, H.L.; Gerard, P.D.; Gill, D.A.

2003-01-01

We measured the importance of 24 fishing site attributes to Mississippi freshwater anglers. Factor analysis identified four multiattribute factors as important in the selection of fishing location: CLEAN ENVIRONMENT CATCH, COST AND HARVEST and AMENITIES AND SAFETY. In general, the importance of site selection factors differed little among anglers grouped by preferred type of fish, preferred fishing location (lakes and reservoirs, rivers and streams, ponds, or reservoir tailwaters), usual manner of fishing (engine-powered boat, nonpowered boat, or shore), or change in fishing frequency. COST AND HARVEST was more important to anglers with high harvest orientations. We found low correlations between site selection factor importance scores and angler age, fishing frequency, fishing expenditures, or fishing motivation factors. We suggest that the general lack of differences in site selection factors among angler groups indicates that management strategies to improve fishing site attributes should benefit all angler groups. Clean fishing environments and awareness of the availability of desired sport fishes were "very" or "extremely" important to fishing site selection by more than 70% of Mississippi freshwater anglers and should be priority management objectives.

Life cycle thinking and assessment tools on environmentally-benign electronics: Convergent optimization of materials use, end-of-life strategy and environmental policies

NASA Astrophysics Data System (ADS)

Zhou, Xiaoying

The purpose of this study is to integrate the quantitative environmental performance assessment tools and the theory of multi-objective optimization within the boundary of electronic product systems to support the selection among design alternatives in terms of environmental impact, technical criteria, and economic feasibility. To meet with the requirements that result from emerging environmental legislation targeting electronics products, the research addresses an important analytical methodological approach to facilitate environmentally conscious design and end-of-life management with a life cycle viewpoint. A synthesis of diverse assessment tools is applied on a set of case studies: lead-free solder materials selection, cellular phone design, and desktop display technology assessment. In the first part of this work, an in-depth industrial survey of the status and concerns of the U.S. electronics industry on the elimination of lead (Pb) in solders is described. The results show that the trade-offs among environmental consequences, technology challenges, business risks, legislative compliance and stakeholders' preferences must be explicitly, simultaneously, and systematically addressed in the decision-making process used to guide multi-faceted planning of environmental solutions. In the second part of this work, the convergent optimization of the technical cycle, economic cycle and environmental cycle is addressed in a coherent and systematic way using the application of environmentally conscious design of cellular phones. The technical understanding of product structure, components analysis, and materials flow facilitates the development of "Design for Disassembly" guidelines. A bottom-up disassembly analysis on a "bill of materials" based structure at a micro-operational level is utilized to select optimal end-of-life strategies on the basis of economic feasibility. A macro-operational level life cycle model is used to investigate the environmental consequences linking environmental impact with the cellular phone production activities focusing on the upstream manufacturing and end-of-life life cycle stages. The last part of this work, the quantitative elicitation of weighting factors facilitates the comparison of trade-offs in the context of a multi-attribute problem. An integrated analytical approach, Integrated Industrial Ecology Function Deployment (I2-EFD), is proposed to assess alternatives at the design phase of a product system and is validated with the assessment of desktop display technologies and lead-free solder alternatives.

Fingerprint Analysis: Moving Toward Multiattribute Determination via Individual Markers.

PubMed

Brunelle, Erica; Huynh, Crystal; Alin, Eden; Eldridge, Morgan; Le, Anh Minh; Halámková, Lenka; Halámek, Jan

2018-01-02

Forensic science will be forever revolutionized if law enforcement can identify personal attributes of a person of interest solely from a fingerprint. For the past 2 years, the goal of our group has been to establish a way to identify originator attributes, specifically biological sex, from a single analyte. To date, an enzymatic assay and two chemical assays have been developed for the analysis of multiple analytes. In this manuscript, two additional assays have been developed. This time, however, the assays utilize only one amino acid each. The enzymatic assay targets alanine and employs alanine transaminase (ALT), pyruvate oxidase (POx), and horseradish peroxidase (HRP). The other, a chemical assay, is known as the Sakaguchi test and targets arginine. It is important to note that alanine has a significantly higher concentration than arginine in the fingerprint content of both males and females. Both assays proved to be capable of accurately differentiating between male and female fingerprints, regardless of their respective average concentration. The ability to target a single analyte will transform forensic science as each originator attribute can be correlated to a different analyte. This would then lead to the possibility of identifying multiple attributes from a single fingerprint sample. Ultimately, this would allow for a profile of a person of interest to be established without the need for time-consuming lab processes.

Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview.

PubMed

Mühlbacher, Axel C; Kaczynski, Anika; Zweifel, Peter; Johnson, F Reed

2016-12-01

Best-worst scaling (BWS), also known as maximum-difference scaling, is a multiattribute approach to measuring preferences. BWS aims at the analysis of preferences regarding a set of attributes, their levels or alternatives. It is a stated-preference method based on the assumption that respondents are capable of making judgments regarding the best and the worst (or the most and least important, respectively) out of three or more elements of a choice-set. As is true of discrete choice experiments (DCE) generally, BWS avoids the known weaknesses of rating and ranking scales while holding the promise of generating additional information by making respondents choose twice, namely the best as well as the worst criteria. A systematic literature review found 53 BWS applications in health and healthcare. This article expounds possibilities of application, the underlying theoretical concepts and the implementation of BWS in its three variants: 'object case', 'profile case', 'multiprofile case'. This paper contains a survey of BWS methods and revolves around study design, experimental design, and data analysis. Moreover the article discusses the strengths and weaknesses of the three types of BWS distinguished and offered an outlook. A companion paper focuses on special issues of theory and statistical inference confronting BWS in preference measurement.

Latin American Clinical Epidemiology Network Series - Paper 4: Economic evaluation of Kangaroo Mother Care: cost utility analysis of results from a randomized controlled trial conducted in Bogotá.

PubMed

Ruiz, Juan Gabriel; Charpak, Nathalie; Castillo, Mario; Bernal, Astrid; Ríos, John; Trujillo, Tammy; Córdoba, María Adelaida

2017-06-01

Although kangaroo mother care (KMC) has been shown to be safe and effective in randomized controlled trials (RCTs), there are no published complete economic evaluations including the three components of the full intervention. A cost utility analysis performed on the results of an RCT conducted in Bogotá, Colombia between 1993 and 1996. Hospital and ambulatory costs were estimated by microcosting in a sample of preterm infants from a University Hospital in Bogotá in 2011 and at a KMC clinic in the same period. Utility scores were assigned by experts by means of (1) direct ordering and scoring discrete health states and (2) constructing a multi-attribute utility function. Ninety-five percent confidence intervals (CIs) for the incremental cost-utility ratios (ICURs) were computed by the Fiellers theorem method. One-way sensitivity analysis on price estimates for valuing costs was performed. ICUR at 1 year of corrected age was $ -1,546 per extra quality-adjusted life year gained using the KMC method (95% CI $ -7,963 to $ 4,910). In Bogotá, the use of KMC is dominant: more effective and cost-saving. Although results from an economic analysis should not be extrapolated to different systems and communities, this dominant result suggests that KMC could be cost-effective in similar low and middle income countries settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Conjoint analysis applications in health--a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force.

PubMed

Bridges, John F P; Hauber, A Brett; Marshall, Deborah; Lloyd, Andrew; Prosser, Lisa A; Regier, Dean A; Johnson, F Reed; Mauskopf, Josephine

2011-06-01

The application of conjoint analysis (including discrete-choice experiments and other multiattribute stated-preference methods) in health has increased rapidly over the past decade. A wider acceptance of these methods is limited by an absence of consensus-based methodological standards. The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Good Research Practices for Conjoint Analysis Task Force was established to identify good research practices for conjoint-analysis applications in health. The task force met regularly to identify the important steps in a conjoint analysis, to discuss good research practices for conjoint analysis, and to develop and refine the key criteria for identifying good research practices. ISPOR members contributed to this process through an extensive consultation process. A final consensus meeting was held to revise the article using these comments, and those of a number of international reviewers. Task force findings are presented as a 10-item checklist covering: 1) research question; 2) attributes and levels; 3) construction of tasks; 4) experimental design; 5) preference elicitation; 6) instrument design; 7) data-collection plan; 8) statistical analyses; 9) results and conclusions; and 10) study presentation. A primary question relating to each of the 10 items is posed, and three sub-questions examine finer issues within items. Although the checklist should not be interpreted as endorsing any specific methodological approach to conjoint analysis, it can facilitate future training activities and discussions of good research practices for the application of conjoint-analysis methods in health care studies. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Reversing the similarity effect: The effect of presentation format.

PubMed

Cataldo, Andrea M; Cohen, Andrew L

2018-06-01

A context effect is a change in preference that occurs when alternatives are added to a choice set. Models of preferential choice that account for context effects largely assume a within-dimension comparison process. It has been shown, however, that the format in which a choice set is presented can influence comparison strategies. That is, a by-alternative or by-dimension grouping of the dimension values encourage within-alternative or within-dimension comparisons, respectively. For example, one classic context effect, the compromise effect, is strengthened by a by-dimension presentation format. Extrapolation from this result suggests that a second context effect, the similarity effect, will actually reverse when stimuli are presented in a by-dimension format. In the current study, we presented participants with a series of apartment choice sets designed to elicit the similarity effect, with either a by-alternative or by-dimension presentation format. Participants in the by-alternative condition demonstrated a standard similarity effect; however, participants in the by-dimension condition demonstrated a strong reverse similarity effect. The present data can be accounted for by Multialternative Decision Field Theory (MDFT) and the Multiattribute Linear Ballistic Accumulator (MLBA), but not Elimination by Aspects (EBA). Indeed, when some weak assumptions of within-dimension processes are met, MDFT and the MLBA predict the reverse similarity effect. These modeling results suggest that the similarity effect is governed by either forgetting and inhibition (MDFT), or attention to positive or negative differences (MLBA). These results demonstrate that flexibility in the comparison process needs to be incorporated into theories of preferential choice. Copyright © 2018 Elsevier B.V. All rights reserved.

Differential Weighting in Multi-Attribute Utility Measurement: When it Should Not and When it does make a Difference

DTIC Science & Technology

1976-08-01

of the motoring public. "The design should balance and optimize characteristics serving environmental, safety, and conservation goals " (McDonald...59 9,738 165 Datsun 610 58 4,766 82 Buick Century 55 5,558 101 Mazda RX4 54 5,207 96 Volkswagen Rabbit 54 4,353 81 AMC Matador 53 4,837 91 Toyota...53 Ford Maverick 8 92 4,229 46 ANMC Hornet 6 94 4,127 44 A’X Pacer 95 4,569 48 Audi Fox 96 5,678 59 Mazda RX4 96 5,207 54 Toyota Corona MIK II 98

Development of the Veritas plot and its application in cardiac surgery: an evidence-synthesis graphic tool for the clinician to assess multiple meta-analyses reporting on a common outcome.

PubMed

Panesar, Sukhmeet S; Rao, Christopher; Vecht, Joshua A; Mirza, Saqeb B; Netuveli, Gopalakrishnan; Morris, Richard; Rosenthal, Joe; Darzi, Ara; Athanasiou, Thanos

2009-10-01

Meta-analyses may be prone to generating misleading results because of a paucity of experimental studies (especially in surgery); publication bias; and heterogeneity in study design, intervention and the patient population of included studies. When investigating a specific clinical or scientific question on which several relevant meta-analyses may have been published, value judgments must be applied to determine which analysis represents the most robust evidence. These value judgments should be specifically acknowledged. We designed the Veritas plot to explicitly explore important elements of quality and to facilitate decision-making by highlighting specific areas in which meta-analyses are found to be deficient. Furthermore, as a graphic tool, it may be more intuitive than when similar data are presented in a tabular or text format. The Veritas plot is an adaption of the radar plot, a graphic tool for the description of multiattribute data. Key elements of meta-analytical quality such as heterogeneity, publication bias and study design are assessed. Existing qualitative methods such as the Assessment of Multiple Systematic Reviews (AMSTAR) tool have been incorporated in addition to important considerations when interpreting surgical meta-analyses such as the year of publication and population characteristics. To demonstrate the potential of the Veritas plot to inform clinical practice, we apply the Veritas plot to the meta-analytical literature comparing the incidence of 30-day stroke in off-pump coronary artery bypass surgery and conventional coronary artery bypass surgery. We demonstrate that a visually-stimulating and practical evidence-synthesis tool can direct the clinician and scientist to a particular meta-analytical study to inform clinical practice. The Veritas plot is also cumulative and allowed us to assess the quality of evidence over time. We have presented a practical graphic application for scientists and clinicians to identify and interpret variability in meta-analyses. Although further validation of the Veritas plot is required, it may have the potential to contribute to the implementation of evidence-based practice.

Monitoring and assessment of anthropogenic activities in mountain lakes: a case of the Fifth Triglav Lake in the Julian Alps.

PubMed

Ravnikar, Tina; Bohanec, Marko; Muri, Gregor

2016-04-01

The Fifth Triglav Lake is a remote mountain lake in the Julian Alps. The area of the Julian Alps where the lake is situated is protected by law and lies within the Triglav National Park. Mountain lakes in Slovenia were considered for a long time as pristine, unpolluted lakes, but analyses in the last decade revealed considerable human impact even in such remote places. Eutrophication or excessive accumulation of nutrients is the main problem of most lakes in the temperate climatic zone, also in Slovenia. Since the introduction of fish in 1991, the lake is going through a series of changes for which we do not know exactly where they lead, so the monitoring and assessment of anthropogenic activities are of great importance. For this purpose, a qualitative multiattribute decision model was developed with DEX method to assess ecological effects on the lake. The extent of the ecological effects on the lake is assessed using four main parameters: the trophic state, lake characteristics, environmental parameters, and anthropogenic stressors. Dependence of environmental impact on various external factors beyond human control, such as temperature, precipitation, retention time, and factors on which we have influence, such as the amount of wastewater and the presence of fish in the lake, were also evaluated. The following data were measured: chlorophyll a, nutrients, TP, oxygen, C/N ratio, nutrients in sediment, temperature, precipitation, retention time, and volume. We made assumptions about fish and wastewater, which we could not measure. The main contributions of this work are the designed model and the obtained findings for the Fifth Triglav Lake that can help not only scientists in understanding the complexity of lake-watershed systems and interactions among system components but also local authorities to manage and monitor the lake aquatic environment in an effective and efficient way. The model is flexible and can be also used for other lakes, assuming that the used parameters are measured and anthropogenic stressors are adjusted to a specific situation. The results of assessment are of particular interest for decision makers in protected areas, providing a new approach to the management of the quality of the water environment.

Cooperation driven coherence: Brains working hard together.

PubMed

Bezerianos, Anastasios; Sun, Yu; Chen, Yu; Woong, Kian Fong; Taya, Fumihiko; Arico, Pietro; Borghini, Gianluca; Babiloni, Fabio; Thakor, Nitish

2015-01-01

The current study aims to look at the difference in coupling of EEG activity of participant pairs while they perform a cooperative, concurrent, independent yet different task at high and low difficulty levels. Participants performed the National Aeronautics and Space Administration (NASA) designed Multi-Attribute Task Battery (MATB-II) task which simulates a pilot and copilot operating an aircraft. Each participant in the pair was responsible for 2 out of 4 subtasks which were independent and different from one another while all tasks occurs concurrently in real time with difficulty levels being the frequency that adjustments are required for each subtask. We found that as the task become more difficult, there was more coupling between the pilot and copilot.

Weighted Description Logics Preference Formulas for Multiattribute Negotiation

NASA Astrophysics Data System (ADS)

Ragone, Azzurra; di Noia, Tommaso; Donini, Francesco M.; di Sciascio, Eugenio; Wellman, Michael P.

We propose a framework to compute the utility of an agreement w.r.t a preference set in a negotiation process. In particular, we refer to preferences expressed as weighted formulas in a decidable fragment of First-order Logic and agreements expressed as a formula. We ground our framework in Description Logics (DL) endowed with disjunction, to be compliant with Semantic Web technologies. A logic based approach to preference representation allows, when a background knowledge base is exploited, to relax the often unrealistic assumption of additive independence among attributes. We provide suitable definitions of the problem and present algorithms to compute utility in our setting. We also validate our approach through an experimental evaluation.

Australian health-related quality of life population norms derived from the SF-6D.

PubMed

Norman, Richard; Church, Jody; van den Berg, Bernard; Goodall, Stephen

2013-02-01

To investigate population health-related quality of life norms in an Australian general sample by age, gender, BMI, education and socioeconomic status. The SF-36 was included in the 2009/10 wave of the Household, Income and Labour Dynamics in Australia (HILDA) survey (n=17,630 individuals across 7,234 households), and converted into SF-6D utility scores. Trends across the various population subgroups were investigated employing population weights to ensure a balanced panel, and were all sub-stratified by gender. SF-6D scores decline with age beyond 40 years, with decreasing education and by higher levels of socioeconomic disadvantage. Scores were also lower at very low and very high BMI levels. Males reported higher SF-6D scores than females across most analyses. This study reports Australian population utility data measured using the SF-6D, based on a national representative sample. These results can be used in a range of policy settings such as cost-utility analysis or exploration of health-related inequality. In general, the patterns are similar to those reported using other multi-attribute utility instruments and in different countries. © 2013 The Authors. ANZJPH © 2013 Public Health Association of Australia.

Risk Preferences, Probability Weighting, and Strategy Tradeoffs in Wildfire Management.

PubMed

Hand, Michael S; Wibbenmeyer, Matthew J; Calkin, David E; Thompson, Matthew P

2015-10-01

Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey-based experiment administered to federal wildfire managers. Respondents were presented with a multiattribute lottery-choice experiment where each lottery is defined by three outcome attributes: expenditures for fire suppression, damage to private property, and exposure of firefighters to the risk of aviation-related fatalities. Respondents choose one of two strategies, each of which includes "good" (low cost/low damage) and "bad" (high cost/high damage) outcomes that occur with varying probabilities. The choice task also incorporates an information framing experiment to test whether information about fatality risk to firefighters alters managers' responses to risk. Results suggest that managers exhibit risk aversion and nonlinear probability weighting, which can result in choices that do not minimize expected expenditures, property damage, or firefighter exposure. Information framing tends to result in choices that reduce the risk of aviation fatalities, but exacerbates nonlinear probability weighting. © 2015 Society for Risk Analysis.

Mirage events & driver haptic steering alerts in a motion-base driving simulator: A method for selecting an optimal HMI.

PubMed

Talamonti, Walter; Tijerina, Louis; Blommer, Mike; Swaminathan, Radhakrishnan; Curry, Reates; Ellis, R Darin

2017-11-01

This paper describes a new method, a 'mirage scenario,' to support formative evaluation of driver alerting or warning displays for manual and automated driving. This method provides driving contexts (e.g., various Times-To-Collision (TTCs) to a lead vehicle) briefly presented and then removed. In the present study, during each mirage event, a haptic steering display was evaluated. This haptic display indicated a steering response may be initiated to drive around an obstacle ahead. A motion-base simulator was used in a 32-participant study to present vehicle motion cues similar to the actual application. Surprise was neither present nor of concern, as it would be for a summative evaluation of a forward collision warning system. Furthermore, no collision avoidance maneuvers were performed, thereby reducing the risk of simulator sickness. This paper illustrates the mirage scenario procedures, the rating methods and definitions used with the mirage scenario, and analysis of the ratings obtained, together with a multi-attribute utility theory (MAUT) approach to evaluate and select among alternative designs for future summative evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Underestimation of Variance of Predicted Health Utilities Derived from Multiattribute Utility Instruments.

PubMed

Chan, Kelvin K W; Xie, Feng; Willan, Andrew R; Pullenayegum, Eleanor M

2017-04-01

Parameter uncertainty in value sets of multiattribute utility-based instruments (MAUIs) has received little attention previously. This false precision leads to underestimation of the uncertainty of the results of cost-effectiveness analyses. The aim of this study is to examine the use of multiple imputation as a method to account for this uncertainty of MAUI scoring algorithms. We fitted a Bayesian model with random effects for respondents and health states to the data from the original US EQ-5D-3L valuation study, thereby estimating the uncertainty in the EQ-5D-3L scoring algorithm. We applied these results to EQ-5D-3L data from the Commonwealth Fund (CWF) Survey for Sick Adults ( n = 3958), comparing the standard error of the estimated mean utility in the CWF population using the predictive distribution from the Bayesian mixed-effect model (i.e., incorporating parameter uncertainty in the value set) with the standard error of the estimated mean utilities based on multiple imputation and the standard error using the conventional approach of using MAUI (i.e., ignoring uncertainty in the value set). The mean utility in the CWF population based on the predictive distribution of the Bayesian model was 0.827 with a standard error (SE) of 0.011. When utilities were derived using the conventional approach, the estimated mean utility was 0.827 with an SE of 0.003, which is only 25% of the SE based on the full predictive distribution of the mixed-effect model. Using multiple imputation with 20 imputed sets, the mean utility was 0.828 with an SE of 0.011, which is similar to the SE based on the full predictive distribution. Ignoring uncertainty of the predicted health utilities derived from MAUIs could lead to substantial underestimation of the variance of mean utilities. Multiple imputation corrects for this underestimation so that the results of cost-effectiveness analyses using MAUIs can report the correct degree of uncertainty.

Cost-Effectiveness of Four Parenting Programs and Bibliotherapy for Parents of Children with Conduct Problems.

PubMed

Sampaio, Filipa; Enebrink, Pia; Mihalopoulos, Cathrine; Feldman, Inna

2016-12-01

Parenting programs and self-help parenting interventions employing written materials are effective in reducing child conduct problems (CP) in the short-term compared to control groups, however evidence on the cost-effectiveness of such interventions is insufficient. Few studies have looked at the differences in effects between interventions in the same study design. This study aimed to determine the cost-effectiveness of four parenting programs: Comet, Incredible Years (IY), Cope and Connect, and bibliotherapy, compared to a waitlist control (WC), with a time horizon of 4 months, targeting CP in children aged 3-12 years. This economic evaluation was conducted alongside an RCT of the four parenting interventions and bibliotherapy compared to a WC. The study sample consisted of 961 parents of 3-12 year-old children with CP. CP was measured by the Eyberg Child Behavior Inventory. Effectiveness was expressed as the proportion of "recovered" cases of CP. The time horizon of the study was four months with a limited health sector perspective, including parents' time costs. We performed an initial comparative cost analysis for interventions whose outcomes differed significantly from the WC, and later a cost-effectiveness analysis of interventions whose outcomes differed significantly from both the WC and each other. Secondary analyses were performed: (i) joint outcome "recovered and improved", (ii) intervention completers, (iii) exclusion of parents' time costs, (iv) exclusion of training costs. All interventions apart from Connect significantly reduced CP compared to the WC. Of the other interventions Comet resulted in a significantly higher proportion of recovered cases compared to bibliotherapy. A comparative cost analysis of the effective interventions rendered an average cost per recovered case for bibliotherapy of USD 483, Cope USD 1972, Comet USD 3741, and IY USD 6668. Furthermore, Comet had an ICER of USD 8375 compared to bibliotherapy. Secondary analyses of "recovered and improved" and of intervention completers held Cope as the cheapest alternative. Exclusion of parents' time and training costs did not change the cost-effectiveness results. The time horizon for this evaluation is very short. This study also had a limited costing perspective. Results may be interpreted with caution when considering decision-making about value for money. The inclusion of a multi-attribute utility instrument sensitive to domains of quality-of-life impacted by CP in children would be valuable so that pragmatic value for money estimations can be made. Further studies are needed with longer follow-up periods to ascertain on the sustainability of the effects, and fuller economic evaluations and economic modeling to provide insights on longer-term cost-effectiveness. These results also raise the need to investigate the cost-effectiveness of the provision of these interventions as a "stepped care" approach. The results suggest the delivery of different programs according to budget constraints and the outcome desired. In the absence of a WTP threshold, bibliotherapy could be a cheap and effective option to initially target CP within a limited budget, whereas Comet could be offered to achieve greater effects based on decision-makers' willingness to make larger investments. In its turn, Cope could be offered when targeting broader outcomes, such as symptom improvement, rather than clinical caseness.

Validation of a multi-criteria evaluation model for animal welfare.

PubMed

Martín, P; Czycholl, I; Buxadé, C; Krieter, J

2017-04-01

The aim of this paper was to validate an alternative multi-criteria evaluation system to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. This alternative methodology aimed to be more transparent for stakeholders and more flexible than the methodology proposed by WQ. The WQ assessment protocol for growing pigs was implemented to collect data in different farms in Schleswig-Holstein, Germany. In total, 44 observations were carried out. The aggregation system proposed in the WQ protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first two steps of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion and principle. The utility functions and the aggregation function were constructed in two separated steps. The MACBETH (Measuring Attractiveness by a Categorical-Based Evaluation Technique) method was used for utility function determination and the Choquet integral (CI) was used as an aggregation operator. The WQ decision-makers' preferences were fitted in order to construct the utility functions and to determine the CI parameters. The validation of the MAUT model was divided into two steps, first, the results of the model were compared with the results of the WQ project at criteria and principle level, and second, a sensitivity analysis of our model was carried out to demonstrate the relative importance of welfare measures in the different steps of the multi-criteria aggregation process. Using the MAUT, similar results were obtained to those obtained when applying the WQ protocol aggregation methods, both at criteria and principle level. Thus, this model could be implemented to produce an overall assessment of animal welfare in the context of the WQ protocol for growing pigs. Furthermore, this methodology could also be used as a framework in order to produce an overall assessment of welfare for other livestock species. Two main findings are obtained from the sensitivity analysis, first, a limited number of measures had a strong influence on improving or worsening the level of welfare at criteria level and second, the MAUT model was not very sensitive to an improvement in or a worsening of single welfare measures at principle level. The use of weighted sums and the conversion of disease measures into ordinal scores should be reconsidered.

Designing a Successful Bidding Strategy Using Fuzzy Sets and Agent Attitudes

NASA Astrophysics Data System (ADS)

Ma, Jun; Goyal, Madhu Lata

To be successful in a multi-attribute auction, agents must be capable of adapting to continuously changing bidding price. This chapter presents a novel fuzzy attitude-based bidding strategy (FA-Bid), which employs dual assessment technique, i.e., assessment of multiple attributes of the goods as well as assessment of agents' attitude (eagerness) to procure an item in automated auction. The assessment of attributes adapts the fuzzy sets technique to handle uncertainty of the bidding process as well use heuristic rules to determine the attitude of bidding agents in simulated auctions to procure goods. The overall assessment is used to determine a price range based on current bid, which finally selects the best one as the new bid.

Seismic Reservoir Characterization for Assessment of CO2 EOR at the Mississippian Reservoir in South-Central Kansas

NASA Astrophysics Data System (ADS)

Tsoflias, G. P.; Graham, B.; Haga, L.; Watney, L.

2017-12-01

The Mississippian in Kansas and Oklahoma is a highly heterogeneous, fractured, oil producing reservoir with thickness typically below seismic resolution. At Wellington field in south-central Kansas CO2 was injected in the Mississippian reservoir for enhanced oil recovery. This study examines the utility of active source surface seismic for characterization of Mississippian reservoir properties and monitoring CO2. Analysis of post-stack 3D seismic data showed the expected response of a gradational transition (ramp velocity) where thicker reservoir units corresponded with lower reflection amplitudes, lower frequency and a 90o phase change. Reflection amplitude could be correlated to reservoir thickness. Pre-stack gather analysis showed that porosity zones of the Mississippian reservoir exhibit characteristic AVO response. Simultaneous AVO inversion estimated P- and S-Impedances, which along with formation porosity logs and post-stack seismic data attributes were incorporated in multi-attribute linear-regression analysis and predicted reservoir porosity with an overall correlation of 0.90 to well data. The 3D survey gather azimuthal anisotropy analysis (AVAZ) provided information on the fault and fracture network and showed good agreement to the regional stress field and well data. Mississippian reservoir porosity and fracture predictions agreed well with the observed mobility of the CO2 in monitoring wells. Fluid substitution modeling predicted acoustic impedance reduction in the Mississippian carbonate reservoir introduced by the presence of CO2. Future work includes the assessment of time-lapse seismic, acquired after the injection of CO2. This work demonstrates that advanced seismic interpretation methods can be used successfully for characterization of the Mississippian reservoir and monitoring of CO2.

Demographics of reintroduced populations: estimation, modeling, and decision analysis

USGS Publications Warehouse

Converse, Sarah J.; Moore, Clinton T.; Armstrong, Doug P.

2013-01-01

Reintroduction can be necessary for recovering populations of threatened species. However, the success of reintroduction efforts has been poorer than many biologists and managers would hope. To increase the benefits gained from reintroduction, management decision making should be couched within formal decision-analytic frameworks. Decision analysis is a structured process for informing decision making that recognizes that all decisions have a set of components—objectives, alternative management actions, predictive models, and optimization methods—that can be decomposed, analyzed, and recomposed to facilitate optimal, transparent decisions. Because the outcome of interest in reintroduction efforts is typically population viability or related metrics, models used in decision analysis efforts for reintroductions will need to include population models. In this special section of the Journal of Wildlife Management, we highlight examples of the construction and use of models for informing management decisions in reintroduced populations. In this introductory contribution, we review concepts in decision analysis, population modeling for analysis of decisions in reintroduction settings, and future directions. Increased use of formal decision analysis, including adaptive management, has great potential to inform reintroduction efforts. Adopting these practices will require close collaboration among managers, decision analysts, population modelers, and field biologists.

Understanding The Decision Context: DPSIR, Decision Landscape, And Social Network Analysis

EPA Science Inventory

Establishing the decision context for a management problem is the critical first step for effective decision analysis. Understanding the decision context allow stakeholders and decision-makers to integrate the societal, environmental, and economic considerations that must be con...

The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World's Largest Open Source Data Sets

NASA Astrophysics Data System (ADS)

Piburn, J.; Stewart, R.; Myers, A.; Sorokine, A.; Axley, E.; Anderson, D.; Burdette, J.; Biddle, C.; Hohl, A.; Eberle, R.; Kaufman, J.; Morton, A.

2017-10-01

Spatiotemporal (ST) analytics applied to major data sources such as the World Bank and World Health Organization has shown tremendous value in shedding light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. WSTAMP engages this opportunity by situating analysts, data, and analytics together within a visually rich and computationally rigorous online analysis environment. Since introducing WSTAMP at the First International Workshop on Spatiotemporal Computing, several transformative advances have occurred. Collaboration with human computer interaction experts led to a complete interface redesign that deeply immerses the analyst within a ST context, significantly increases visual and textual content, provides navigational crosswalks for attribute discovery, substantially reduce mouse and keyboard actions, and supports user data uploads. Secondly, the database has been expanded to include over 16,000 attributes, 50 years of time, and 200+ nation states and redesigned to support non-annual, non-national, city, and interaction data. Finally, two new analytics are implemented for analyzing large portfolios of multi-attribute data and measuring the behavioral stability of regions along different dimensions. These advances required substantial new approaches in design, algorithmic innovations, and increased computational efficiency. We report on these advances and inform how others may freely access the tool.

Advancing Alternative Analysis: Integration of Decision Science.

PubMed

Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina M; Blake, Ann; Carroll, William F; Corbett, Charles J; Hansen, Steffen Foss; Lempert, Robert J; Linkov, Igor; McFadden, Roger; Moran, Kelly D; Olivetti, Elsa; Ostrom, Nancy K; Romero, Michelle; Schoenung, Julie M; Seager, Thomas P; Sinsheimer, Peter; Thayer, Kristina A

2017-06-13

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings. We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. We advance four recommendations: a ) engaging the systematic development and evaluation of decision approaches and tools; b ) using case studies to advance the integration of decision analysis into alternatives analysis; c ) supporting transdisciplinary research; and d ) supporting education and outreach efforts. https://doi.org/10.1289/EHP483.

The South Florida Ecosystem Portfolio Model - A Map-Based Multicriteria Ecological, Economic, and Community Land-Use Planning Tool

USGS Publications Warehouse

Labiosa, William B.; Bernknopf, Richard; Hearn, Paul; Hogan, Dianna; Strong, David; Pearlstine, Leonard; Mathie, Amy M.; Wein, Anne M.; Gillen, Kevin; Wachter, Susan

2009-01-01

The South Florida Ecosystem Portfolio Model (EPM) prototype is a regional land-use planning Web tool that integrates ecological, economic, and social information and values of relevance to decision-makers and stakeholders. The EPM uses a multicriteria evaluation framework that builds on geographic information system-based (GIS) analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to regional land-use/land-cover (LULC) change. The EPM uses both economics (monetized) and multiattribute utility (nonmonetized) approaches to valuing these endpoints and consequences. This hybrid approach represents a methodological middle ground between rigorous economic and ecological/ environmental scientific approaches. The EPM sacrifices some degree of economic- and ecological-forecasting precision to gain methodological transparency, spatial explicitness, and transferability, while maintaining credibility. After all, even small steps in the direction of including ecosystem services evaluation are an improvement over current land-use planning practice (Boyd and Wainger, 2003). There are many participants involved in land-use decision-making in South Florida, including local, regional, State, and Federal agencies, developers, environmental groups, agricultural groups, and other stakeholders (South Florida Regional Planning Council, 2003, 2004). The EPM's multicriteria evaluation framework is designed to cut across the objectives and knowledge bases of all of these participants. This approach places fundamental importance on social equity and stakeholder participation in land-use decision-making, but makes no attempt to determine normative socially 'optimal' land-use plans. The EPM is thus a map-based set of evaluation tools for planners and stakeholders to use in their deliberations of what is 'best', considering a balancing of disparate interests within a regional perspective. Although issues of regional ecological sustainability can be explored with the EPM (for example, changes in biodiversity potential and regional habitat fragmentation), it does not attempt to define or evaluate long-term ecological sustainability as such. Instead, the EPM is intended to provide transparent first-order indications of the direction of ecological, economic, and community change, not to make detailed predictions of ecological, economic, and social outcomes. In short, the EPM is an attempt to widen the perspectives of its users by integrating natural and social scientific information in a framework that recognizes the diversity of values at stake in South Florida land-use planning. For terrestrial ecosystems, land-cover change is one of the most important direct drivers of changes in ecosystem services (Hassan and others, 2005). More specifically, the fragmentation of habitat from expanding low-density development across landscapes appears to be a major driver of terrestrial species decline and the impairment of terrestrial ecosystem integrity, in some cases causing irreversible impairment from a land-use planning perspective (Brody, 2008; Peck, 1998). Many resource managers and land-use planners have come to realize that evaluating land-use conversions on a parcel-by-parcel basis leads to a fragmented and narrow view of the regional effects of natural land-cover loss to development (Marsh and Lallas, 1995). The EPM is an attempt to integrate important aspects of the coupled natural-system/human-system view from a regional planning perspective. The EPM evaluates proposed land-use changes, both conversion and intensification, in terms of relevant ecological, economic, and social criteria that combine information about probable land-use outcomes, based on ecological and environmental models, as well as value judgments, as expressed in user-modifiable preference models. Based on on-going meetings and interviews with stakeholders and potential tool users we foc

Choice Rules and Accumulator Networks

PubMed Central

2015-01-01

This article presents a preference accumulation model that can be used to implement a number of different multi-attribute heuristic choice rules, including the lexicographic rule, the majority of confirming dimensions (tallying) rule and the equal weights rule. The proposed model differs from existing accumulators in terms of attribute representation: Leakage and competition, typically applied only to preference accumulation, are also assumed to be involved in processing attribute values. This allows the model to perform a range of sophisticated attribute-wise comparisons, including comparisons that compute relative rank. The ability of a preference accumulation model composed of leaky competitive networks to mimic symbolic models of heuristic choice suggests that these 2 approaches are not incompatible, and that a unitary cognitive model of preferential choice, based on insights from both these approaches, may be feasible. PMID:28670592

Alternative electrical distribution system architectures for automobiles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Afridi, K.K.; Tabors, R.D.; Kassakian, J.G.

At present most automobiles use a 12 V electrical system with point-to-point wiring. The capability of this architecture in meeting the needs of future electrical loads is questionable. Furthermore, with the development of electric vehicles (EVs) there is a greater need for a better architecture. In this paper the authors outline the limitations of the conventional architecture and identify alternatives. They also present a multi-attribute trade-off methodology which compares these alternatives, and identifies a set of Pareto optimal architectures. The system attributes traded off are cost, weight, losses and probability of failure. These are calculated by a computer program thatmore » has built-in component attribute models. System attributes of a few dozen architectures are also reported and the results analyzed. 17 refs.« less

Improving multi-tasking ability through action videogames.

PubMed

Chiappe, Dan; Conger, Mark; Liao, Janet; Caldwell, J Lynn; Vu, Kim-Phuong L

2013-03-01

The present study examined whether action videogames can improve multi-tasking in high workload environments. Two groups with no action videogame experience were pre-tested using the Multi-Attribute Task Battery (MATB). It consists of two primary tasks; tracking and fuel management, and two secondary tasks; systems monitoring and communication. One group served as a control group, while a second played action videogames a minimum of 5 h a week for 10 weeks. Both groups returned for a post-assessment on the MATB. We found the videogame treatment enhanced performance on secondary tasks, without interfering with the primary tasks. Our results demonstrate action videogames can increase people's ability to take on additional tasks by increasing attentional capacity. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Understanding medical decision making in hand surgery.

PubMed

Myers, John; McCabe, Steven J

2005-10-01

The practice of medicine takes place in an environment of uncertainty. Expected value decision making, prospect theory, and regret theory are three theories of decision making under uncertainty that may be used to help us learn how patients and physicians make decisions. These theories form the underpinnings of decision analysis and provide the opportunity to introduce the broad discipline of decision science. Because decision analysis and economic analysis are underrepresented in upper extremity surgery, the authors believe these are important areas for future research.

Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers

PubMed Central

Vickers, Andrew J; Cronin, Angel M; Elkin, Elena B; Gonen, Mithat

2008-01-01

Background Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques. Methods In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques. Results Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve. Conclusion Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided. PMID:19036144

Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers.

PubMed

Vickers, Andrew J; Cronin, Angel M; Elkin, Elena B; Gonen, Mithat

2008-11-26

Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques. In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques. Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve. Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided.

The potential for meta-analysis to support decision analysis in ecology.

PubMed

Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

2015-06-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.

Advancing Alternative Analysis: Integration of Decision Science

PubMed Central

Zaunbrecher, Virginia M.; Batteate, Christina M.; Blake, Ann; Carroll, William F.; Corbett, Charles J.; Hansen, Steffen Foss; Lempert, Robert J.; Linkov, Igor; McFadden, Roger; Moran, Kelly D.; Olivetti, Elsa; Ostrom, Nancy K.; Romero, Michelle; Schoenung, Julie M.; Seager, Thomas P.; Sinsheimer, Peter; Thayer, Kristina A.

2017-01-01

Background: Decision analysis—a systematic approach to solving complex problems—offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. Objectives: We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. Methods: A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups’ findings. Results: We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. Conclusions: We advance four recommendations: a) engaging the systematic development and evaluation of decision approaches and tools; b) using case studies to advance the integration of decision analysis into alternatives analysis; c) supporting transdisciplinary research; and d) supporting education and outreach efforts. https://doi.org/10.1289/EHP483 PMID:28669940

Walking the Fine Line: Political Decision Making with or without Data.

ERIC Educational Resources Information Center

Merkel-Keller, Claudia

The stages of the policy process are examined and explained in terms of the decision making framework. The policy process is comprised of four stages; policy analysis, policy formation, policy decision, and political analysis. Political analysis is the performance of the market analysis needed for a decision. The political weight, rather than the…

Decision fatigue: A conceptual analysis.

PubMed

Pignatiello, Grant A; Martin, Richard J; Hickman, Ronald L

2018-03-01

Decision fatigue is an applicable concept to healthcare psychology. Due to a lack of conceptual clarity, we present a concept analysis of decision fatigue. A search of the term "decision fatigue" was conducted across seven research databases, which yielded 17 relevant articles. The authors identified three antecedent themes (decisional, self-regulatory, and situational) and three attributional themes (behavioral, cognitive, and physiological) of decision fatigue. However, the extant literature failed to adequately describe consequences of decision fatigue. This concept analysis provides needed conceptual clarity for decision fatigue, a concept possessing relevance to nursing and allied health sciences.

Applications of decision analysis and related techniques to industrial engineering problems at KSC

NASA Technical Reports Server (NTRS)

Evans, Gerald W.

1995-01-01

This report provides: (1) a discussion of the origination of decision analysis problems (well-structured problems) from ill-structured problems; (2) a review of the various methodologies and software packages for decision analysis and related problem areas; (3) a discussion of how the characteristics of a decision analysis problem affect the choice of modeling methodologies, thus providing a guide as to when to choose a particular methodology; and (4) examples of applications of decision analysis to particular problems encountered by the IE Group at KSC. With respect to the specific applications at KSC, particular emphasis is placed on the use of the Demos software package (Lumina Decision Systems, 1993).

HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: PUBLISHED REPORT

EPA Science Inventory

NRMRL-CIN-1351A Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. EPA/600/R-01/104 (NTIS PB2002-102119). Decision makers using environmental decision support tools are often ...

The Risky Shift in Policy Decision Making: A Comparative Analysis

ERIC Educational Resources Information Center

Wilpert, B.; And Others

1976-01-01

Based on analysis of data on 432 decision-makers from around the world, this study examines the decision-making phenomenon that individuals tend to move toward riskier decisions after group discussion. Findings of the analysis contradicted earlier studies, showing a consistent shift toward greater risk avoidance. Available from Elsevier Scientific…

Decision analysis in clinical cardiology: When is coronary angiography required in aortic stenosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Georgeson, S.; Meyer, K.B.; Pauker, S.G.

1990-03-15

Decision analysis offers a reproducible, explicit approach to complex clinical decisions. It consists of developing a model, typically a decision tree, that separates choices from chances and that specifies and assigns relative values to outcomes. Sensitivity analysis allows exploration of alternative assumptions. Cost-effectiveness analysis shows the relation between dollars spent and improved health outcomes achieved. In a tutorial format, this approach is applied to the decision whether to perform coronary angiography in a patient who requires aortic valve replacement for critical aortic stenosis.

Considering Risk and Resilience in Decision-Making

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2015-01-01

This paper examines the concepts of decision-making, risk analysis, uncertainty and resilience analysis. The relation between risk, vulnerability, and resilience is analyzed. The paper describes how complexity, uncertainty, and ambiguity are the most critical factors in the definition of the approach and criteria for decision-making. Uncertainty in its various forms is what limits our ability to offer definitive answers to questions about the outcomes of alternatives in a decision-making process. It is shown that, although resilience-informed decision-making would seem fundamentally different from risk-informed decision-making, this is not the case as resilience-analysis can be easily incorporated within existing analytic-deliberative decision-making frameworks.

HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: JOURNAL ARTICLE

EPA Science Inventory

NRMRL-CIN-1351 Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. Risk Analysis 600/R/01/104, Available: on internet, www.epa.gov/ORD/NRMRL/Pubs/600R01104, [NET]. 03/07/2001 D...

Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites.

PubMed

Khadam, Ibrahim; Kaluarachchi, Jagath J

2003-07-01

Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating non-technical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed.

Model-based system-of-systems engineering for space-based command, control, communication, and information architecture design

NASA Astrophysics Data System (ADS)

Sindiy, Oleg V.

This dissertation presents a model-based system-of-systems engineering (SoSE) approach as a design philosophy for architecting in system-of-systems (SoS) problems. SoS refers to a special class of systems in which numerous systems with operational and managerial independence interact to generate new capabilities that satisfy societal needs. Design decisions are more complicated in a SoS setting. A revised Process Model for SoSE is presented to support three phases in SoS architecting: defining the scope of the design problem, abstracting key descriptors and their interrelations in a conceptual model, and implementing computer-based simulations for architectural analyses. The Process Model enables improved decision support considering multiple SoS features and develops computational models capable of highlighting configurations of organizational, policy, financial, operational, and/or technical features. Further, processes for verification and validation of SoS models and simulations are also important due to potential impact on critical decision-making and, thus, are addressed. Two research questions frame the research efforts described in this dissertation. The first concerns how the four key sources of SoS complexity---heterogeneity of systems, connectivity structure, multi-layer interactions, and the evolutionary nature---influence the formulation of SoS models and simulations, trade space, and solution performance and structure evaluation metrics. The second question pertains to the implementation of SoSE architecting processes to inform decision-making for a subset of SoS problems concerning the design of information exchange services in space-based operations domain. These questions motivate and guide the dissertation's contributions. A formal methodology for drawing relationships within a multi-dimensional trade space, forming simulation case studies from applications of candidate architecture solutions to a campaign of notional mission use cases, and executing multi-purpose analysis studies is presented. These efforts are coupled to the generation of aggregate and time-dependent solution performance metrics via the hierarchical decomposition of objectives and the analytical recomposition of multi-attribute qualitative program drivers from quantifiable measures. This methodology was also applied to generate problem-specific solution structure evaluation metrics that facilitate the comparison of alternate solutions at a high level of aggregation, at lower levels of abstraction, and to relate options for design variables with associated performance values. For proof-of-capability demonstration, the selected application problem concerns the design of command, control, communication, and information (C3I) architecture services for a notional campaign of crewed and robotic lunar surface missions. The impetus for the work was the demonstration of using model-based SoSE for design of sustainable interoperability capabilities between all data and communication assets in extended lunar campaigns. A comprehensive Lunar C3I simulation tool was developed by a team of researchers at Purdue University in support of NASA's Constellation Program; the author of this dissertation was a key contributor to the creation of this tool and made modifications and extensions to key components relevant to the methodological concepts presented in this dissertation. The dissertation concludes with a presentation of example results based on the interrogation of the constructed Lunar C3I computational model. The results are based on a family of studies, structured around a trade-tree of architecture options, which were conducted to test the hypothesis that the SoSE approach is efficacious in the information-exchange architecture design in space exploration domain. Included in the family of proof-of-capability studies is a simulation of the Apollo 17 mission, which allows not only for partial verification and validation of the model, but also provides insights for prioritizing future model design iterations to make it more realistic representation of the "real world." A caveat within the results presented is that they serve within the capacity of a proof-of-capability demonstration, and as such, they are a product of models and analyses that need further development before the tool's results can be employed for decision-making. Additional discussion is provided for how to further develop and validate the Lunar C3I tool and also to make it extensible to other SoS design problems of similar nature in space exploration and other problem application domains.

Measuring site-level success in brownfield redevelopments: a focus on sustainability and green building.

PubMed

Wedding, G Christopher; Crawford-Brown, Douglas

2007-10-01

This research has met the following four objectives within the broader research topic of characterizing and quantifying success in brownfield revitalization: (1) to define 40 total indicators that define and determine the success of brownfield redevelopments in four categories: environment-health, finance, livability, and social-economic; (2) to use these indicators to develop a partially automated tool that stakeholders in brownfield redevelopment may use to more easily assess and communicate success (or failures) in these projects; (3) to integrate "green" building as an important aspect of successful brownfield redevelopments; and (4) to develop this tool within the framework of a specific multi-attribute decision method (MADM), the analytical hierarchical process (AHP). Future research should include the operationalization and application of this tool to specific sites. Currently, no such indicator framework or automated tool is known to exist or be in use. Indicators were chosen because of their ability to reduce data into comprehensible measurements and to systematically measure success in a standardized fashion. Appropriate indicators were selected based on (1) interviews with prominent private developers and national leaders in brownfield redevelopment, (2) a review of the relevant literature, (3) objective hierarchies created in this project, and (4) the ability for each indicator to serve goals in more than one of the four categories described above. These were combined to form the Sustainable Brownfields Redevelopment (SBR) Tool. A survey was conducted to serve as a preliminary assessment and proposed methodology for judging the validity of the SBR Tool. Professionals in the academic, private, and public sector were asked to provide an evaluation of the management tool and a weighting of the relative importance of each indicator and each of the four categories listed previously. Experts rated the tool at 7.68 out of 10 suggesting that this framework will be useful in evaluating these redevelopments upon completion and in formulating initial site plans and building design.

Interaction between active tectonics, erosion and diapirism, a case study from Habble-Rud in Southern Central Alborz (Northern Iran)

NASA Astrophysics Data System (ADS)

Jaberi, Maryam; Ghassemi, Mohammad R.; Shayan, Siavosh; Yamani, Mojtaba; Zamanzadeh, Seyed Mohammad

2018-01-01

The Alborz mountain chain is a region of active deformation within the Arabia-Eurasia continental collision zone. The southern part of central Alborz Mountains, in the north of Iran, represents complex tectonics because it is located at the border of two developing continental sedimentary basins between southern central Alborz and Central Iran. An arid and semi-arid climate, a large extent of Quaternary sediments, rugged topography, salt domes and faults with historical seismicity influence the Habble-Rud River catchment. In the present research, a number of tectonic geomorphologic indices were extracted from satellite imagery and 10 m DEM (digital elevation model) data in order to identify relative tectonic activity within the basin. The indices include: stream length-gradient index (Sl), drainage basin asymmetry (Af), index of mountain front sinuosity (Smf), hypsometric integral (Hi), index of drainage basin shape (Bs), ratio of valley-floor width to valley height (Vf), and fault density (Fd). Due to the presence of heterogeneous indices for all sections of the catchment causing large extension of Habble-Rud (3260 km2), all of the variables such as extremely erodible formations, faults and folds and salt tectonics on the Southern part; were put into a matrix table. As a new approach, the variables were put into the SAW (simple additive model) model as one of MADM (multi-attribute decision-making models) techniques. The study area was divided into four regions according to the values of SAW. These classes include very high (%11), high (48.3%), moderate (34.7%), and low activity (3.4%). The result of the model suggests that the study area is located on a changing tectonic trend in central Alborz from NW-SE to NE-SW. The regions with high relative tectonic activity in HR catchment correspond to the active Garmsar and Sorkhe-Kalout faults and diapirs.

An attentional theory of emotional influences on risky decisions.

PubMed

Levine, Daniel S; Ramirez, Patrick A

2013-01-01

It is well known that choices between gambles can depend not only on the probabilities of gains or losses but also on the emotional richness of the items to be gained or lost. Rottenstreich and Hsee (2001) demonstrated that overweighting of low probabilities is magnified if the possible events are emotionally rich, such as a kiss versus an amount of money. Ramirez (2010) showed that persistence in the face of comparable numerically presented losses is greater when the scenario involves taking care of a pet (emotionally richer) versus a business (emotionally poorer). Much of this phenomenon is captured in a neural network model of the Rottenstreich-Hsee data (Levine, 2012). The model is based on interactions among the orbitofrontal cortex, amygdala, cingulate, striatum, thalamus, and premotor cortex that implement categorization of multiattribute vectors representing choice options, in a manner consistent with the gists of fuzzy trace theory. Before categorization, the vectors are weighted by selective attention to attributes that are either emotionally salient or task relevant, with increasing emotional arousal shifting the attentional weights away from numerical attributes such as precise probabilities. This interpretation is supported by the data of Hsee and Rottenstreich (2004) showing that how much participants would pay to save endangered animals is not influenced by the number to be saved if they see pictures but is influenced by the number if they are given verbal descriptions. The theory suggests a few open questions. How are the selective attentional signals represented in the interactions between prefrontal cortex and subcortical areas? Would the salience of numerical attributes still be reduced with high arousal in highly numerate participants? Would the differences between the pet and business scenarios be altered if the positive or negative feedback participants received were shown via pictures rather than numbers? Copyright © 2013 Elsevier B.V. All rights reserved.

The need for consumer behavior analysis in health care coverage decisions.

PubMed

Thompson, A M; Rao, C P

1990-01-01

Demographic analysis has been the primary form of analysis connected with health care coverage decisions. This paper reviews past demographic research and shows the need to use behavioral analyses for health care coverage policy decisions. A behavioral model based research study is presented and a case is made for integrated study into why consumers make health care coverage decisions.

Toward Reflective Judgment in Exploratory Factor Analysis Decisions: Determining the Extraction Method and Number of Factors To Retain.

ERIC Educational Resources Information Center

Knight, Jennifer L.

This paper considers some decisions that must be made by the researcher conducting an exploratory factor analysis. The primary purpose is to aid the researcher in making informed decisions during the factor analysis instead of relying on defaults in statistical programs or traditions of previous researchers. Three decision areas are addressed.…

Do violations of the axioms of expected utility theory threaten decision analysis?

PubMed

Nease, R F

1996-01-01

Research demonstrates that people violate the independence principle of expected utility theory, raising the question of whether expected utility theory is normative for medical decision making. The author provides three arguments that violations of the independence principle are less problematic than they might first appear. First, the independence principle follows from other more fundamental axioms whose appeal may be more readily apparent than that of the independence principle. Second, the axioms need not be descriptive to be normative, and they need not be attractive to all decision makers for expected utility theory to be useful for some. Finally, by providing a metaphor of decision analysis as a conversation between the actual decision maker and a model decision maker, the author argues that expected utility theory need not be purely normative for decision analysis to be useful. In short, violations of the independence principle do not necessarily represent direct violations of the axioms of expected utility theory; behavioral violations of the axioms of expected utility theory do not necessarily imply that decision analysis is not normative; and full normativeness is not necessary for decision analysis to generate valuable insights.

Distinction between Externally vs. Internally Guided Decision-Making: Operational Differences, Meta-Analytical Comparisons and Their Theoretical Implications

PubMed Central

Nakao, Takashi; Ohira, Hideki; Northoff, Georg

2012-01-01

Most experimental studies of decision-making have specifically examined situations in which a single less-predictable correct answer exists (externally guided decision-making under uncertainty). Along with such externally guided decision-making, there are instances of decision-making in which no correct answer based on external circumstances is available for the subject (internally guided decision-making). Such decisions are usually made in the context of moral decision-making as well as in preference judgment, where the answer depends on the subject’s own, i.e., internal, preferences rather than on external, i.e., circumstantial, criteria. The neuronal and psychological mechanisms that allow guidance of decisions based on more internally oriented criteria in the absence of external ones remain unclear. This study was undertaken to compare decision-making of these two kinds empirically and theoretically. First, we reviewed studies of decision-making to clarify experimental–operational differences between externally guided and internally guided decision-making. Second, using multi-level kernel density analysis, a whole-brain-based quantitative meta-analysis of neuroimaging studies was performed. Our meta-analysis revealed that the neural network used predominantly for internally guided decision-making differs from that for externally guided decision-making under uncertainty. This result suggests that studying only externally guided decision-making under uncertainty is insufficient to account for decision-making processes in the brain. Finally, based on the review and results of the meta-analysis, we discuss the differences and relations between decision-making of these two types in terms of their operational, neuronal, and theoretical characteristics. PMID:22403525

Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making. Copyright © 2016. Published by Elsevier Inc.

Preferences for tap water attributes within couples: An exploration of alternative mixed logit parameterizations

NASA Astrophysics Data System (ADS)

Scarpa, Riccardo; Thiene, Mara; Hensher, David A.

2012-01-01

Preferences for attributes of complex goods may differ substantially among members of households. Some of these goods, such as tap water, are jointly supplied at the household level. This issue of jointness poses a series of theoretical and empirical challenges to economists engaged in empirical nonmarket valuation studies. While a series of results have already been obtained in the literature, the issue of how to empirically measure these differences, and how sensitive the results are to choice of model specification from the same data, is yet to be clearly understood. In this paper we use data from a widely employed form of stated preference survey for multiattribute goods, namely choice experiments. The salient feature of the data collection is that the same choice experiment was applied to both partners of established couples. The analysis focuses on models that simultaneously handle scale as well as preference heterogeneity in marginal rates of substitution (MRS), thereby isolating true differences between members of couples in their MRS, by removing interpersonal variation in scale. The models employed are different parameterizations of the mixed logit model, including the willingness to pay (WTP)-space model and the generalized multinomial logit model. We find that in this sample there is some evidence of significant statistical differences in values between women and men, but these are of small magnitude and only apply to a few attributes.

Behavioral Modeling of Adversaries with Multiple Objectives in Counterterrorism.

PubMed

Mazicioglu, Dogucan; Merrick, Jason R W

2018-05-01

Attacker/defender models have primarily assumed that each decisionmaker optimizes the cost of the damage inflicted and its economic repercussions from their own perspective. Two streams of recent research have sought to extend such models. One stream suggests that it is more realistic to consider attackers with multiple objectives, but this research has not included the adaption of the terrorist with multiple objectives to defender actions. The other stream builds off experimental studies that show that decisionmakers deviate from optimal rational behavior. In this article, we extend attacker/defender models to incorporate multiple objectives that a terrorist might consider in planning an attack. This includes the tradeoffs that a terrorist might consider and their adaption to defender actions. However, we must also consider experimental evidence of deviations from the rationality assumed in the commonly used expected utility model in determining such adaption. Thus, we model the attacker's behavior using multiattribute prospect theory to account for the attacker's multiple objectives and deviations from rationality. We evaluate our approach by considering an attacker with multiple objectives who wishes to smuggle radioactive material into the United States and a defender who has the option to implement a screening process to hinder the attacker. We discuss the problems with implementing such an approach, but argue that research in this area must continue to avoid misrepresenting terrorist behavior in determining optimal defensive actions. © 2017 Society for Risk Analysis.

Demand assessment and price-elasticity estimation of quality-improved primary health care in Palestine: a contribution from the contingent valuation method.

PubMed

Mataria, Awad; Luchini, Stéphane; Daoud, Yousef; Moatti, Jean-Paul

2007-10-01

This paper proposes a new methodology to assess demand and price-elasticity for health care, based on patients' stated willingness to pay (WTP) values for certain aspects of health care quality improvements. A conceptual analysis of how respondents consider contingent valuation (CV) questions allowed us to specify a probability density function of stated WTP values, and consequently, to model a demand function for quality-improved health care, using a parametric survival approach. The model was empirically estimated using a CV study intended to assess patients' values for improving the quality of primary health care (PHC) services in Palestine. A random sample of 499 individuals was interviewed following medical consultation in four PHC centers. Quality was assessed using a multi-attribute approach; and respondents valued seven specific quality improvements using a decomposed valuation scenario and a payment card elicitation technique. Our results suggest an inelastic demand at low user fees levels, and when the price-increase is accompanied with substantial quality-improvements. Nevertheless, demand becomes more and more elastic if user fees continue to rise. On the other hand, patients' reactions to price-increase turn out to depend on their level of income. Our results can be used to design successful health care financing strategies that include a consideration of patients' preferences and financial capacities. John Wiley & Sons, Ltd.

DECISION ANALYSIS OF INCINERATION COSTS IN SUPERFUND SITE REMEDIATION

EPA Science Inventory

This study examines the decision-making process of the remedial design (RD) phase of on-site incineration projects conducted at Superfund sites. Decisions made during RD affect the cost and schedule of remedial action (RA). Decision analysis techniques are used to determine the...

Issue a Boil-Water Advisory or Wait for Definitive Information? A Decision Analysis

PubMed Central

Wagner, Michael M.; Wallstrom, Garrick L.; Onisko, Agnieszka

2005-01-01

Objective Study the decision to issue a boil-water advisory in response to a spike in sales of diarrhea remedies or wait 72 hours for the results of definitive testing of water and people. Methods Decision analysis. Results In the base-case analysis, the optimal decision is test-and-wait. If the cost of issuing a boil-water advisory is less than 13.92 cents per person per day, the optimal decision is to issue the boil-water advisory immediately. Conclusions Decisions based on surveillance data that are suggestive but not conclusive about the existence of a disease outbreak can be modeled. PMID:16779145

75 FR 35457 - Draft of the 2010 Causal Analysis/Diagnosis Decision Information System (CADDIS)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-22

... Causal Analysis/Diagnosis Decision Information System (CADDIS) AGENCY: Environmental Protection Agency... site, ``2010 release of the Causal Analysis/Diagnosis Decision Information System (CADDIS).'' The... analyses, downloadable software tools, and links to outside information sources. II. How to Submit Comments...

Multicriteria decision analysis: Overview and implications for environmental decision making

USGS Publications Warehouse

Hermans, Caroline M.; Erickson, Jon D.; Erickson, Jon D.; Messner, Frank; Ring, Irene

2007-01-01

Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

NASA Astrophysics Data System (ADS)

Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

2012-12-01

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.

Development of Automated Aids for Decision Analysis

DTIC Science & Technology

1976-05-01

21 7. Resources Affected by a Decision .. ................... 22 8. Scope of Decision ..................................... 22 9. Urgency...24 t . Resources Available for Analysis . . . .. . . . 26 Expeiene anTrininginAayigDcsos2 C. Chrceisiso heDcso Poes2 -I. II TYPES OF DECISION...Assessment . . . . . . . . . ......... . 62 a. Assessing State Variables .... ........... ... 63 b. Assessing Dependencics .. . .. ... . 65 c. Assessing

Helping decision makers frame, analyze, and implement decisions

USGS Publications Warehouse

Runge, Michael C.; McDonald-Madden, Eve

2018-01-01

All decisions have the same recognizable elements. Context, objectives, alternatives, consequences, and deliberation. Decision makers and analysts familiar with these elements can quickly see the underlying structure of a decision.There are only a small number of classes of decisions. These classes differ in the cognitive and scientific challenge they present to the decision maker; the ability to recognize the class of decision leads a decision maker to tools to aid in the analysis.Sometimes we need more information, sometimes we don’t. The role of science in a decision-making process is to provide the predictions that link the alternative actions to the desired outcomes. Investing in more science is only valuable if it helps to choose a better action.Implementation. The successful integration of decision analysis into environmental decisions requires careful attention to the decision, the people, and the institutions involved.

Economic evaluation of the DiAMOND randomized trial: cost and outcomes of 2 decision aids for mode of delivery among women with a previous cesarean section.

PubMed

Hollinghurst, Sandra; Emmett, Clare; Peters, Tim J; Watson, Helen; Fahey, Tom; Murphy, Deirdre J; Montgomery, Alan

2010-01-01

Maternal preferences should be considered in decisions about mode of delivery following a previous cesarean, but risks and benefits are unclear. Decision aids can help decision making, although few studies have assessed costs in conjunction with effectiveness. Economic evaluation of 2 decision aids for women with 1 previous cesarean. Cost-consequences analysis. Data sources were self-reported resource use and outcome and published national unit costs. The target population was women with 1 previous cesarean. The time horizon was 37 weeks' gestation and 6 weeks postnatal. The perspective was health care delivery system. The interventions were usual care, usual care plus an information program, and usual care plus a decision analysis program. The outcome measures were costs to the National Health Service (NHS) in the United Kingdom (UK), score on the Decisional Conflict Scale, and mode of delivery. RESULTS OF MAIN ANALYSIS: Cost of delivery represented 84% of the total cost; mode of delivery was the most important determinant of cost differences across the groups. Mean (SD) total cost per mother and baby: 2033 (677) for usual care, 2069 (738) for information program, and 2019 (741) for decision analysis program. Decision aids reduced decisional conflict. Women using the decision analysis program had fewest cesarean deliveries. Applying a cost premium to emergency cesareans over electives had little effect on group comparisons. Conclusions were unaffected. Disparity in timing of outcomes and costs, data completeness, and quality. Decision aids can reduce decisional conflict in women with a previous cesarean section when deciding on mode of delivery. The information program could be implemented at no extra cost to the NHS. The decision analysis program might reduce the rate of cesarean sections without any increase in costs.

Characterizing uncertain sea-level rise projections to support investment decisions.

PubMed

Sriver, Ryan L; Lempert, Robert J; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.

Characterizing uncertain sea-level rise projections to support investment decisions

PubMed Central

Lempert, Robert J.; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions. PMID:29414978

Data for Renewable Energy Planning, Policy, and Investment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, Sarah L

Reliable, robust, and validated data are critical for informed planning, policy development, and investment in the clean energy sector. The Renewable Energy (RE) Explorer was developed to support data-driven renewable energy analysis that can inform key renewable energy decisions globally. This document presents the types of geospatial and other data at the core of renewable energy analysis and decision making. Individual data sets used to inform decisions vary in relation to spatial and temporal resolution, quality, and overall usefulness. From Data to Decisions, a complementary geospatial data and analysis decision guide, provides an in-depth view of these and other considerationsmore » to enable data-driven planning, policymaking, and investment. Data support a wide variety of renewable energy analyses and decisions, including technical and economic potential assessment, renewable energy zone analysis, grid integration, risk and resiliency identification, electrification, and distributed solar photovoltaic potential. This fact sheet provides information on the types of data that are important for renewable energy decision making using the RE Data Explorer or similar types of geospatial analysis tools.« less

Automatic Generation of Heuristics for Scheduling

NASA Technical Reports Server (NTRS)

Morris, Robert A.; Bresina, John L.; Rodgers, Stuart M.

1997-01-01

This paper presents a technique, called GenH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing consensus that heuristics encode advice that is, at best, useful in solving most, or typical, problem instances, and, at worst, useful in solving only a narrowly defined set of instances. In either case, heuristic problem solvers, to be broadly applicable, should have a means of automatically adjusting to the idiosyncrasies of each problem instance. GenH generates a search heuristic for a given problem instance by hill-climbing in the space of possible multi-attribute heuristics, where the evaluation of a candidate heuristic is based on the quality of the solution found under its guidance. We present empirical results obtained by applying GenH to the real world problem of telescope observation scheduling. These results demonstrate that GenH is a simple and effective way of improving the performance of an heuristic scheduler.

Multi-Attribute Strategy and Performance Architectures in R&D: The Case of The Balanced Scorecard

DTIC Science & Technology

2006-03-01

learning.    We also found that balance, accessibility, transparency, and participation are increasingly  being  seen  as desirable features of the strategy...project would have never  seen  the light of the day. I am especially  thankful to Steven Popper for giving me the confidence to take on this challenging...among a ranking of 16 R&D  related problems perceived by the members for two years, 1993 & 1995 (Ellis, 1997.)  Traditionally R&D was  seen  as a rather

[Digital radiography in young children. Considerations based on experiences in practice].

PubMed

Berkhout, W E R; Mileman, P A; Weerheijm, K L

2004-10-01

In dentistry, digital radiology techniques, such as a charge-coupled device and a storage phosphor plate, are gaining popularity. It was the objective of this study to assess the importance of the advantages and disadvantages of digital radiology techniques for bitewing radiography in young children, when compared to conventional film. A group of dentists received a questionnaire regarding their experiences with digital radiology techniques or conventional films among young children. Using the Simple Multi-Attributive Rating Technique (SMART) a final weighted score was calculated for the charge-coupled device, the phosphor plate, and conventional film. The scores were 7.40, 7.38, and 6.98 respectively. The differences were not statistically significant (p > 0.47). It could be concluded that, on the basis of experiences in practice, there are no statistically significant preferences for the use of digital radioogy techniques for bitewing radiography in young children.

The value of decision tree analysis in planning anaesthetic care in obstetrics.

PubMed

Bamber, J H; Evans, S A

2016-08-01

The use of decision tree analysis is discussed in the context of the anaesthetic and obstetric management of a young pregnant woman with joint hypermobility syndrome with a history of insensitivity to local anaesthesia and a previous difficult intubation due to a tongue tumour. The multidisciplinary clinical decision process resulted in the woman being delivered without complication by elective caesarean section under general anaesthesia after an awake fibreoptic intubation. The decision process used is reviewed and compared retrospectively to a decision tree analytical approach. The benefits and limitations of using decision tree analysis are reviewed and its application in obstetric anaesthesia is discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Naturalistic Decision Making: Implications for Design

DTIC Science & Technology

1993-04-01

Cognitive Task Analysis Decision Making Design Engineer Design System Human-Computer Interface System Development 15. NUMBER OF PAGES 182 16...people use to select a course of action. The SOAR explains how stress affects the decision making of both individuals and teams. COGNITIVE TASK ANALYSIS : This...procedures for Cognitive Task Analysis , contrasting the strengths and weaknesses of each, and showing how a Cognitive Task Analysis

Decision curve analysis for assessing the usefulness of tests for making decisions to treat: an application to tests for prodromal psychosis.

PubMed

Pulleyblank, Ryan; Chuma, Jefter; Gilbody, Simon M; Thompson, Carl

2013-09-01

For a test to be considered useful for making treatment decisions, it is necessary that making treatment decisions based on the results of the test be a preferable strategy to making treatment decisions without the test. Decision curve analysis is a framework for assessing when a test would be expected to be useful, which integrates evidence of a test's performance characteristics (sensitivity and specificity), condition prevalence among at-risk patients, and patient preferences for treatment. We describe decision curve analysis generally and illustrate its potential through an application to tests for prodromal psychosis. Clinical psychosis is often preceded by a prodromal phase, but not all those with prodromal symptoms proceed to develop full psychosis. Patients identified as at risk for developing psychosis may be considered for proactive treatment to mitigate development of clinically defined psychosis. Tests exist to help identify those at-risk patients most likely to develop psychosis, but it is uncertain when these tests would be considered useful for making proactive treatment decisions. We apply decision curve analysis to results from a systematic review of studies investigating clinical tests for predicting the development of psychosis in at-risk populations, and present resulting decision curves that illustrate when the tests may be expected to be useful for making proactive treatment decisions.

An Analysis of Factors that Influence Enlistment Decisions in the U.S. Army

DTIC Science & Technology

1998-03-01

NAVAL POSTGRADUATE SCHOOL Monterey, California CM THESIS AN ANALYSIS OF FACTORS THAT INFLUENCE ENLISTMENT DECISIONS IN THE U.S. ARMY by Young...TITLE AND SUBTITLE : AN ANALYSIS OF FACTORS THAT INFLUENCE ENLISTMENT DECISIONS IN THE U.S. ARMY 6. AUTHOR(S) Oh, Young Yeol 7...200 words) The purpose of this thesis is to analyze factors that influence decisions to enlist in the U.S. Army. This thesis uses 1997 New Recruit

To analyse a trace or not? Evaluating the decision-making process in the criminal investigation.

PubMed

Bitzer, Sonja; Ribaux, Olivier; Albertini, Nicola; Delémont, Olivier

2016-05-01

In order to broaden our knowledge and understanding of the decision steps in the criminal investigation process, we started by evaluating the decision to analyse a trace and the factors involved in this decision step. This decision step is embedded in the complete criminal investigation process, involving multiple decision and triaging steps. Considering robbery cases occurring in a geographic region during a 2-year-period, we have studied the factors influencing the decision to submit biological traces, directly sampled on the scene of the robbery or on collected objects, for analysis. The factors were categorised into five knowledge dimensions: strategic, immediate, physical, criminal and utility and decision tree analysis was carried out. Factors in each category played a role in the decision to analyse a biological trace. Interestingly, factors involving information available prior to the analysis are of importance, such as the fact that a positive result (a profile suitable for comparison) is already available in the case, or that a suspect has been identified through traditional police work before analysis. One factor that was taken into account, but was not significant, is the matrix of the trace. Hence, the decision to analyse a trace is not influenced by this variable. The decision to analyse a trace first is very complex and many of the tested variables were taken into account. The decisions are often made on a case-by-case basis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Integration of Propulsion-Airframe-Aeroacoustic Technologies and Design Concepts for a Quiet Blended-Wing-Body Transport

NASA Technical Reports Server (NTRS)

Hill, G. A.; Brown, S. A.; Geiselhart, K. A.

2004-01-01

This paper summarizes the results of studies undertaken to investigate revolutionary propulsion-airframe configurations that have the potential to achieve significant noise reductions over present-day commercial transport aircraft. Using a 300 passenger Blended-Wing-Body (BWB) as a baseline, several alternative low-noise propulsion-airframe-aeroacoustic (PAA) technologies and design concepts were investigated both for their potential to reduce the overall BWB noise levels, and for their impact on the weight, performance, and cost of the vehicle. Two evaluation frameworks were implemented for the assessments. The first was a Multi-Attribute Decision Making (MADM) process that used a Pugh Evaluation Matrix coupled with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This process provided a qualitative evaluation of the PAA technologies and design concepts and ranked them based on how well they satisfied chosen design requirements. From the results of the evaluation, it was observed that almost all of the PAA concepts gave the BWB a noise benefit, but degraded its performance. The second evaluation framework involved both deterministic and probabilistic systems analyses that were performed on a down-selected number of BWB propulsion configurations incorporating the PAA technologies and design concepts. These configurations included embedded engines with Boundary Layer Ingesting Inlets, Distributed Exhaust Nozzles installed on podded engines, a High Aspect Ratio Rectangular Nozzle, Distributed Propulsion, and a fixed and retractable aft airframe extension. The systems analyses focused on the BWB performance impacts of each concept using the mission range as a measure of merit. Noise effects were also investigated when enough information was available for a tractable analysis. Some tentative conclusions were drawn from the results. One was that the Boundary Layer Ingesting Inlets provided improvements to the BWB's mission range, by increasing the propulsive efficiency at cruise, and therefore offered a means to offset performance penalties imposed by some of the advanced PAA configurations. It was also found that the podded Distributed Exhaust Nozzle configuration imposed high penalties on the mission range and the need for substantial synergistic performance enhancements from an advanced integration scheme was identified. The High Aspect Ratio Nozzle showed inconclusive noise results and posed significant integration difficulties. Distributed Propulsion, in general, imposed performance penalties but may offer some promise for noise reduction from jet-to-jet shielding effects. Finally, a retractable aft airframe extension provided excellent noise reduction for a modest decrease in range.

Gathering Real World Evidence with Cluster Analysis for Clinical Decision Support.

PubMed

Xia, Eryu; Liu, Haifeng; Li, Jing; Mei, Jing; Li, Xuejun; Xu, Enliang; Li, Xiang; Hu, Gang; Xie, Guotong; Xu, Meilin

2017-01-01

Clinical decision support systems are information technology systems that assist clinical decision-making tasks, which have been shown to enhance clinical performance. Cluster analysis, which groups similar patients together, aims to separate patient cases into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. Useful as it is, the application of cluster analysis in clinical decision support systems is less reported. Here, we describe the usage of cluster analysis in clinical decision support systems, by first dividing patient cases into similar groups and then providing diagnosis or treatment suggestions based on the group profiles. This integration provides data for clinical decisions and compiles a wide range of clinical practices to inform the performance of individual clinicians. We also include an example usage of the system under the scenario of blood lipid management in type 2 diabetes. These efforts represent a step toward promoting patient-centered care and enabling precision medicine.

An Overview of R in Health Decision Sciences.

PubMed

Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam

2017-10-01

As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.

Models for Rational Decision Making. Analysis of Literature and Selected Bibliography. Analysis and Bibliography Series, No. 6.

ERIC Educational Resources Information Center

Hall, John S.

This review analyzes the trend in educational decision making to replace hierarchical authority structures with more rational models for decision making drawn from management science. Emphasis is also placed on alternatives to a hierarchical decision-making model, including governing models, union models, and influence models. A 54-item…

NASA program decisions using reliability analysis.

NASA Technical Reports Server (NTRS)

Steinberg, A.

1972-01-01

NASA made use of the analytical outputs of reliability people to make management decisions on the Apollo program. Such decisions affected the amount of the incentive fees, how much acceptance testing was necessary, how to optimize development testing, whether to approve engineering changes, and certification of flight readiness. Examples of such analysis are discussed and related to programmatic decisions.-

75 FR 18205 - Notice of Peer Review Meeting for the External Peer Review Drafts of Two Documents on Using...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-09

... Role of Risk Analysis in Decision-Making AGENCY: Environmental Protection Agency (EPA). ACTION: Notice... documents entitled, ``Using Probabilistic Methods to Enhance the Role of Risk Analysis in Decision- Making... Probabilistic Methods to Enhance the Role of Risk Analysis in Decision-Making, with Case Study Examples'' and...

Valuing Health Using Time Trade-Off and Discrete Choice Experiment Methods: Does Dimension Order Impact on Health State Values?

PubMed

Mulhern, Brendan; Shah, Koonal; Janssen, Mathieu F Bas; Longworth, Louise; Ibbotson, Rachel

2016-01-01

Health states defined by multiattribute instruments such as the EuroQol five-dimensional questionnaire with five response levels (EQ-5D-5L) can be valued using time trade-off (TTO) or discrete choice experiment (DCE) methods. A key feature of the tasks is the order in which the health state dimensions are presented. Respondents may use various heuristics to complete the tasks, and therefore the order of the dimensions may impact on the importance assigned to particular states. To assess the impact of different EQ-5D-5L dimension orders on health state values. Preferences for EQ-5D-5L health states were elicited from a broadly representative sample of members of the UK general public. Respondents valued EQ-5D-5L health states using TTO and DCE methods across one of three dimension orderings via face-to-face computer-assisted personal interviews. Differences in mean values and the size of the health dimension coefficients across the arms were compared using difference testing and regression analyses. Descriptive analysis suggested some differences between the mean TTO health state values across the different dimension orderings, but these were not systematic. Regression analysis suggested that the magnitude of the dimension coefficients differs across the different dimension orderings (for both TTO and DCE), but there was no clear pattern. There is some evidence that the order in which the dimensions are presented impacts on the coefficients, which may impact on the health state values provided. The order of dimensions is a key consideration in the design of health state valuation studies. Copyright © 2016. Published by Elsevier Inc.

Vision and Quality of Life Index: validation of the Indian version using Rasch analysis.

PubMed

Gothwal, Vijaya K; Bagga, Deepak K

2013-07-18

A multi-attribute utility instrument (MAUI) consists of a descriptive system in which the items and responses seek information about a concept of the universe of health-related quality of life (QoL), and responses to these items then are weighted and combined to produce the index. To our knowledge, the 6-item Vision and Quality of Life Index (VisQoL) is the only available vision-related MAUI, developed and validated in Australia, specifically for visually impaired (VI) populations. To our knowledge, the psychometric properties of the VisQoL have not yet been investigated in an Indian VI sample; this was the aim of our study. The Indian VisQoL was administered to 349 VI adults face-to-face by a trained interviewer at the Vision Rehabilitation Centres of a tertiary eye care facility, South India. Rasch analysis was used to assess the psychometric properties. Rescoring was necessary for all except one item before ordered thresholds were obtained. All items fit the Rasch model and unidimensionality was confirmed. Person separation was acceptable (2.01), indicating that the instrument can discriminate among three strata of participants" vision-related QoL (VRQoL). The VisQoL items were targeted substantially to the participants" VRQoL (-0.69 logits). One item ("ability to have friendships") demonstrated large differential item functioning by work status; working participants reported the item to be more difficult (-1.13 logits) relative to other items when compared to the nonworking participants. The 6-item Indian VisQoL satisfies unidimensional Rasch model expectations in VI patients. Disordering of response categories was evident; replication is required before a common rescoring option should be considered.

A preliminary study applying decision analysis to the treatment of caries in primary teeth.

PubMed

Tamošiūnas, Vytautas; Kay, Elizabeth; Craven, Rebecca

2013-01-01

To determine an optimal treatment strategy for carious deciduous teeth. Manchester Dental Hospital. Decision analysis. The likelihoods of each of the sequelae of caries in deciduous teeth were determined from the literature. The utility of the outcomes from non-treatment and treatment was then measured in 100 parents of children with caries, using a visual analogue scale. Decision analysis was performed which weighted the value of each potential outcome by the probability of its occurrence. A decision tree "fold-back" and sensitivity analysis then determined which treatment strategies, under which circumstances, offered the maximum expected utilities. The decision to leave a carious deciduous tooth unrestored attracted a maximum utility of 76.65 and the overall expected utility for the decision "restore" was 73.27 The decision to restore or not restore carious deciduous teeth are therefore of almost equal value. The decision is however highly sensitive to the utility value assigned to the advent of pain by the patient. There is no clear advantage to be gained by restoring deciduous teeth if patients' evaluations of outcomes are taken into account. Avoidance of pain and avoidance of procedures which are viewed as unpleasant by parents should be key determinants of clinical decision making about carious deciduous teeth.

When is enough evidence enough? - Using systematic decision analysis and value-of-information analysis to determine the need for further evidence.

PubMed

Siebert, Uwe; Rochau, Ursula; Claxton, Karl

2013-01-01

Decision analysis (DA) and value-of-information (VOI) analysis provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. In medical decision making under uncertainty, there are two fundamental questions: 1) What decision should be made now given the best available evidence (and its uncertainty)?; 2) Subsequent to the current decision and given the magnitude of the remaining uncertainty, should we gather further evidence (i.e., perform additional studies), and if yes, which studies should be undertaken (e.g., efficacy, side effects, quality of life, costs), and what sample sizes are needed? Using the currently best available evidence, VoI analysis focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which the additional information will reduce this uncertainty. A quantitative framework allows for the valuation of the additional information that is generated by further research, and considers the decision maker's objectives and resource constraints. Claxton et al. summarise: "Value of information analysis can be used to inform a range of policy questions including whether a new technology should be approved based on existing evidence, whether it should be approved but additional research conducted or whether approval should be withheld until the additional evidence becomes available." [Claxton K. Value of information entry in Encyclopaedia of Health Economics, Elsevier, forthcoming 2014.] The purpose of this tutorial is to introduce the framework of systematic VoI analysis to guide further research. In our tutorial article, we explain the theoretical foundations and practical methods of decision analysis and value-of-information analysis. To illustrate, we use a simple case example of a foot ulcer (e.g., with diabetes) as well as key references from the literature, including examples for the use of the decision-analytic VoI framework by health technology assessment agencies to guide further research. These concepts may guide stakeholders involved or interested in how to determine whether or not and, if so, which additional evidence is needed to make decisions. Copyright © 2013. Published by Elsevier GmbH.

Decision Modeling for Socio-Cultural Data

DTIC Science & Technology

2011-02-01

REFERENCES [1] Malczewski, J. (1999) GIS and Multicriteria Decision Analysis . John Wiley and Sons, New York. [2] Ehrgott, M., and Gandibleux, X. (Eds...up, nonexclusive, irrevocable worldwide license to use , modify, reproduce, release, perform, display, or disclose the work by or on behalf of the...criteria decision analysis (MCDA), into a geospatial environment to support decision making for campaign management. Our development approach supports

Development of a decision support system for analysis and solutions of prolonged standing in the workplace.

PubMed

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-06-01

Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially.

Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

PubMed Central

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-01-01

Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

PubMed

Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

2018-01-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.

Analysis of the decision-making process of nurse managers: a collective reflection.

PubMed

Eduardo, Elizabete Araujo; Peres, Aida Maris; de Almeida, Maria de Lourdes; Roglio, Karina de Dea; Bernardino, Elizabeth

2015-01-01

to analyze the decision-making model adopted by nurses from the perspective of some decision-making process theories. qualitative approach, based on action research. Semi-structured questionnaires and seminars were conducted from April to June 2012 in order to understand the nature of decisions and the decision-making process of nine nurses in position of managers at a public hospital in Southern Brazil. Data were subjected to content analysis. data were classified in two categories: the current situation of decision-making, which showed a lack of systematization; the construction and collective decision-making, which emphasizes the need to develop a decision-making model. the decision-making model used by nurses is limited because it does not consider two important factors: the limits of human rationality, and the external and internal organizational environments that influence and determine right decisions.

LANL Institutional Decision Support By Process Modeling and Analysis Group (AET-2)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Booth, Steven Richard

2016-04-04

AET-2 has expertise in process modeling, economics, business case analysis, risk assessment, Lean/Six Sigma tools, and decision analysis to provide timely decision support to LANS leading to continuous improvement. This capability is critical during the current tight budgetary environment as LANS pushes to identify potential areas of cost savings and efficiencies. An important arena is business systems and operations, where processes can impact most or all laboratory employees. Lab-wide efforts are needed to identify and eliminate inefficiencies to accomplish Director McMillan’s charge of “doing more with less.” LANS faces many critical and potentially expensive choices that require sound decision supportmore » to ensure success. AET-2 is available to provide this analysis support to expedite the decisions at hand.« less

Decision analysis framing study; in-valley drainage management strategies for the western San Joaquin Valley, California

USGS Publications Warehouse

Presser, Theresa S.; Jenni, Karen E.; Nieman, Timothy; Coleman, James

2010-01-01

Constraints on drainage management in the western San Joaquin Valley and implications of proposed approaches to management were recently evaluated by the U.S. Geological Survey (USGS). The USGS found that a significant amount of data for relevant technical issues was available and that a structured, analytical decision support tool could help optimize combinations of specific in-valley drainage management strategies, address uncertainties, and document underlying data analysis for future use. To follow-up on USGS's technical analysis and to help define a scientific basis for decisionmaking in implementing in-valley drainage management strategies, this report describes the first step (that is, a framing study) in a Decision Analysis process. In general, a Decision Analysis process includes four steps: (1) problem framing to establish the scope of the decision problem(s) and a set of fundamental objectives to evaluate potential solutions, (2) generation of strategies to address identified decision problem(s), (3) identification of uncertainties and their relationships, and (4) construction of a decision support model. Participation in such a systematic approach can help to promote consensus and to build a record of qualified supporting data for planning and implementation. In December 2008, a Decision Analysis framing study was initiated with a series of meetings designed to obtain preliminary input from key stakeholder groups on the scope of decisions relevant to drainage management that were of interest to them, and on the fundamental objectives each group considered relevant to those decisions. Two key findings of this framing study are: (1) participating stakeholders have many drainage management objectives in common; and (2) understanding the links between drainage management and water management is necessary both for sound science-based decisionmaking and for resolving stakeholder differences about the value of proposed drainage management solutions. Citing ongoing legal processes associated with drainage management in the western San Joaquin Valley, the U.S. Bureau of Reclamation (USBR) withdrew from the Decision Analysis process early in the proceedings. Without the involvement of the USBR, the USGS discontinued further development of this study.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies.

PubMed

Rousson, Valentin; Zumbrunn, Thomas

2011-06-22

Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies

PubMed Central

2011-01-01

Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. Methods We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. Results We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. Conclusions We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application. PMID:21696604

Training in Decision-making Strategies: An approach to enhance students' competence to deal with socio-scientific issues

NASA Astrophysics Data System (ADS)

Gresch, Helge; Hasselhorn, Marcus; Bögeholz, Susanne

2013-10-01

Dealing with socio-scientific issues in science classes enables students to participate productively in controversial discussions concerning ethical topics, such as sustainable development. In this respect, well-structured decision-making processes are essential for elaborate reasoning. To foster decision-making competence, a computer-based programme was developed that trains secondary school students (grades 11-13) in decision-making strategies. The main research question is: does training students to use these strategies foster decision-making competence? In addition, the influence of meta-decision aids was examined. Students conducted a task analysis to select an appropriate strategy prior to the decision-making process. Hence, the second research question is: does combining decision-making training with a task analysis enhance decision-making competence at a higher rate? To answer these questions, 386 students were tested in a pre-post-follow-up control-group design that included two training groups (decision-making strategies/decision-making strategies combined with a task analysis) and a control group (decision-making with additional ecological information instead of strategic training). An open-ended questionnaire was used to assess decision-making competence in situations related to sustainable development. The decision-making training led to a significant improvement in the post-test and the follow-up, which was administered three months after the training. Long-term effects on the quality of the students' decisions were evident for both training groups. Gains in competence when reflecting upon the decision-making processes of others were found, to a lesser extent, in the training group that received the additional meta-decision training. In conclusion, training in decision-making strategies is a promising approach to deal with socio-scientific issues related to sustainable development.

Fuzzy rationality and parameter elicitation in decision analysis

NASA Astrophysics Data System (ADS)

Nikolova, Natalia D.; Tenekedjiev, Kiril I.

2010-07-01

It is widely recognised by decision analysts that real decision-makers always make estimates in an interval form. An overview of techniques to find an optimal alternative among such with imprecise and interval probabilities is presented. Scalarisation methods are outlined as most appropriate. A proper continuation of such techniques is fuzzy rational (FR) decision analysis. A detailed representation of the elicitation process influenced by fuzzy rationality is given. The interval character of probabilities leads to the introduction of ribbon functions, whose general form and special cases are compared with the p-boxes. As demonstrated, approximation of utilities in FR decision analysis does not depend on the probabilities, but the approximation of probabilities is dependent on preferences.

A decision analysis approach for risk management of near-earth objects

NASA Astrophysics Data System (ADS)

Lee, Robert C.; Jones, Thomas D.; Chapman, Clark R.

2014-10-01

Risk management of near-Earth objects (NEOs; e.g., asteroids and comets) that can potentially impact Earth is an important issue that took on added urgency with the Chelyabinsk event of February 2013. Thousands of NEOs large enough to cause substantial damage are known to exist, although only a small fraction of these have the potential to impact Earth in the next few centuries. The probability and location of a NEO impact are subject to complex physics and great uncertainty, and consequences can range from minimal to devastating, depending upon the size of the NEO and location of impact. Deflecting a potential NEO impactor would be complex and expensive, and inter-agency and international cooperation would be necessary. Such deflection campaigns may be risky in themselves, and mission failure may result in unintended consequences. The benefits, risks, and costs of different potential NEO risk management strategies have not been compared in a systematic fashion. We present a decision analysis framework addressing this hazard. Decision analysis is the science of informing difficult decisions. It is inherently multi-disciplinary, especially with regard to managing catastrophic risks. Note that risk analysis clarifies the nature and magnitude of risks, whereas decision analysis guides rational risk management. Decision analysis can be used to inform strategic, policy, or resource allocation decisions. First, a problem is defined, including the decision situation and context. Second, objectives are defined, based upon what the different decision-makers and stakeholders (i.e., participants in the decision) value as important. Third, quantitative measures or scales for the objectives are determined. Fourth, alternative choices or strategies are defined. Fifth, the problem is then quantitatively modeled, including probabilistic risk analysis, and the alternatives are ranked in terms of how well they satisfy the objectives. Sixth, sensitivity analyses are performed in order to examine the impact of uncertainties. Finally, the need for further analysis, data collection, or refinement is determined. The first steps of defining the problem and the objectives are critical to constructing an informative decision analysis. Such steps must be undertaken with participation from experts, decision-makers, and stakeholders (defined here as "decision participants"). The basic problem here can be framed as: “What is the best strategy to manage risk associated with NEOs?” Some high-level objectives might be to minimize: mortality and injuries, damage to critical infrastructure (e.g., power, communications and food distribution), ecosystem damage, property damage, ungrounded media and public speculation, resources expended, and overall cost. Another valuable objective would be to maximize inter-agency/government coordination. Some of these objectives (e.g., “minimize mortality”) are readily quantified (e.g., deaths and injuries averted). Others are less so (e.g., “maximize inter-agency/government coordination”), but these can be scaled. Objectives may be inversely related: e.g., a strategy that minimizes mortality may cost more. They are also unlikely to be weighted equally. Defining objectives and assessing their relative weight and interactions requires early engagement with decision participants. High-level decisions include whether to deflect a NEO, when to deflect, what is the best alternative for deflection/destruction, and disaster management strategies if an impact occurs. Important influences include, for example: NEO characteristics (orbital characteristics, diameter, mass, spin and composition), impact probability and location, interval between discovery and projected impact date, interval between discovery and deflection target date, costs of information collection, costs and technological feasibility of deflection alternatives, risks of deflection campaigns, requirements for inter-agency and international cooperation, and timing of informing the public. The analytical aspects of decision analysis center on estimation of the expected value (i.e. utility) of different alternatives. The expected value of an alternative is a function of the probability-weighted consequences, estimated using Bayesian calculations in a decision tree or influence diagram model. The result is a set of expected-value estimates for all alternatives evaluated that enables a ranking; the higher the expected value, the more preferred the alternative. A common way to include resource limitations is by framing the decision analysis in the context of economics (e.g., cost-effectiveness analysis). An important aspect of decision analysis in the NEO risk management case is the ability, known as sensitivity analysis, to examine the effect of parameter uncertainty upon decisions. The simplest way to evaluate uncertainty associated with the information used in a decision analysis is to adjust the input values one at a time (or simultaneously) to examine how the results change. Monte Carlo simulations can be used to adjust the inputs over ranges or distributions of values; statistical means then are used to determine the most influential variables. These techniques yield a measure known as the expected value of imperfect information. This value is highly informative, because it allows the decision-maker with imperfect information to evaluate the impact of using experiments, tests, or data collection (e.g. Earth-based observations, space-based remote sensing, etc.) to refine judgments; and indeed to estimate how much should be spent to reduce uncertainty.

Decision Trajectories in Dementia Care Networks: Decisions and Related Key Events.

PubMed

Groen-van de Ven, Leontine; Smits, Carolien; Oldewarris, Karen; Span, Marijke; Jukema, Jan; Eefsting, Jan; Vernooij-Dassen, Myrra

2017-10-01

This prospective multiperspective study provides insight into the decision trajectories of people with dementia by studying the decisions made and related key events. This study includes three waves of interviews, conducted between July 2010 and July 2012, with 113 purposefully selected respondents (people with beginning to advanced stages of dementia and their informal and professional caregivers) completed in 12 months (285 interviews). Our multilayered qualitative analysis consists of content analysis, timeline methods, and constant comparison. Four decision themes emerged-managing daily life, arranging support, community living, and preparing for the future. Eight key events delineate the decision trajectories of people with dementia. Decisions and key events differ between people with dementia living alone and living with a caregiver. Our study clarifies that decisions relate not only to the disease but to living with the dementia. Individual differences in decision content and sequence may effect shared decision-making and advance care planning.

Group decision making with the analytic hierarchy process in benefit-risk assessment: a tutorial.

PubMed

Hummel, J Marjan; Bridges, John F P; IJzerman, Maarten J

2014-01-01

The analytic hierarchy process (AHP) has been increasingly applied as a technique for multi-criteria decision analysis in healthcare. The AHP can aid decision makers in selecting the most valuable technology for patients, while taking into account multiple, and even conflicting, decision criteria. This tutorial illustrates the procedural steps of the AHP in supporting group decision making about new healthcare technology, including (1) identifying the decision goal, decision criteria, and alternative healthcare technologies to compare, (2) structuring the decision criteria, (3) judging the value of the alternative technologies on each decision criterion, (4) judging the importance of the decision criteria, (5) calculating group judgments, (6) analyzing the inconsistency in judgments, (7) calculating the overall value of the technologies, and (8) conducting sensitivity analyses. The AHP is illustrated via a hypothetical example, adapted from an empirical AHP analysis on the benefits and risks of tissue regeneration to repair small cartilage lesions in the knee.

Conceptualizing surrogate decision making at end of life in the intensive care unit using cognitive task analysis.

PubMed

Dionne-Odom, J Nicholas; Willis, Danny G; Bakitas, Marie; Crandall, Beth; Grace, Pamela J

2015-01-01

Surrogate decision makers (SDMs) face difficult decisions at end of life (EOL) for decisionally incapacitated intensive care unit (ICU) patients. To identify and describe the underlying psychological processes of surrogate decision making for adults at EOL in the ICU. Qualitative case study design using a cognitive task analysis interviewing approach. Participants were recruited from October 2012 to June 2013 from an academic tertiary medical center's ICU located in the rural Northeastern United States. Nineteen SDMs for patients who had died in the ICU completed in-depth semistructured cognitive task analysis interviews. The conceptual framework formulated from data analysis reveals that three underlying, iterative, psychological dimensions (gist impressions, distressing emotions, and moral intuitions) impact an SDM's judgment about the acceptability of either the patient's medical treatments or his or her condition. The framework offers initial insights about the underlying psychological processes of surrogate decision making and may facilitate enhanced decision support for SDMs. Copyright © 2015 Elsevier Inc. All rights reserved.

Incorporating uncertainty regarding applicability of evidence from meta-analyses into clinical decision making.

PubMed

Kriston, Levente; Meister, Ramona

2014-03-01

Judging applicability (relevance) of meta-analytical findings to particular clinical decision-making situations remains challenging. We aimed to describe an evidence synthesis method that accounts for possible uncertainty regarding applicability of the evidence. We conceptualized uncertainty regarding applicability of the meta-analytical estimates to a decision-making situation as the result of uncertainty regarding applicability of the findings of the trials that were included in the meta-analysis. This trial-level applicability uncertainty can be directly assessed by the decision maker and allows for the definition of trial inclusion probabilities, which can be used to perform a probabilistic meta-analysis with unequal probability resampling of trials (adaptive meta-analysis). A case study with several fictitious decision-making scenarios was performed to demonstrate the method in practice. We present options to elicit trial inclusion probabilities and perform the calculations. The result of an adaptive meta-analysis is a frequency distribution of the estimated parameters from traditional meta-analysis that provides individually tailored information according to the specific needs and uncertainty of the decision maker. The proposed method offers a direct and formalized combination of research evidence with individual clinical expertise and may aid clinicians in specific decision-making situations. Copyright © 2014 Elsevier Inc. All rights reserved.

Three-class ROC analysis--the equal error utility assumption and the optimality of three-class ROC surface using the ideal observer.

PubMed

He, Xin; Frey, Eric C

2006-08-01

Previously, we have developed a decision model for three-class receiver operating characteristic (ROC) analysis based on decision theory. The proposed decision model maximizes the expected decision utility under the assumption that incorrect decisions have equal utilities under the same hypothesis (equal error utility assumption). This assumption reduced the dimensionality of the "general" three-class ROC analysis and provided a practical figure-of-merit to evaluate the three-class task performance. However, it also limits the generality of the resulting model because the equal error utility assumption will not apply for all clinical three-class decision tasks. The goal of this study was to investigate the optimality of the proposed three-class decision model with respect to several other decision criteria. In particular, besides the maximum expected utility (MEU) criterion used in the previous study, we investigated the maximum-correctness (MC) (or minimum-error), maximum likelihood (ML), and Nyman-Pearson (N-P) criteria. We found that by making assumptions for both MEU and N-P criteria, all decision criteria lead to the previously-proposed three-class decision model. As a result, this model maximizes the expected utility under the equal error utility assumption, maximizes the probability of making correct decisions, satisfies the N-P criterion in the sense that it maximizes the sensitivity of one class given the sensitivities of the other two classes, and the resulting ROC surface contains the maximum likelihood decision operating point. While the proposed three-class ROC analysis model is not optimal in the general sense due to the use of the equal error utility assumption, the range of criteria for which it is optimal increases its applicability for evaluating and comparing a range of diagnostic systems.

Decision-Making in National Security Affairs: Toward a Typology.

DTIC Science & Technology

1985-06-07

decisional model, and thus provide the necessary linkage between observation and application of theory in explaining and/or predicting policy decisions . r...examines theories and models of decision -making processes from an interdisciplinary perspective, with a view toward deriving means by which the behavior of...processes, game theory , linear programming, network and graph theory , time series analysis, and the like. The discipline of decision analysis is a relatively

Gender and internet consumers' decision-making.

PubMed

Yang, Chyan; Wu, Chia-Chun

2007-02-01

The purpose of this research is to provide managers of shopping websites information regarding consumer purchasing decisions based on the Consumer Styles Inventory (CSI). According to the CSI, one can capture what decision-making styles online shoppers use. Furthermore, this research also discusses the gender differences among online shoppers. Exploratory factor analysis (EFA) was used to understand the decision-making styles and discriminant analysis was used to distinguish the differences between female and male shoppers. The result shows that there are differences in purchasing decisions between online female and male Internet users.

Non-monetary valuation using Multi-Criteria Decision Analysis: Sensitivity of additive aggregation methods to scaling and compensation assumptions

EPA Science Inventory

Analytical methods for Multi-Criteria Decision Analysis (MCDA) support the non-monetary valuation of ecosystem services for environmental decision making. Many published case studies transform ecosystem service outcomes into a common metric and aggregate the outcomes to set land ...

Decision Support Framework Implementation Of The Web-Based Environmental Decision Analysis DASEES: Decision Analysis For A Sustainable Environment, Economy, And Society

EPA Science Inventory

Solutions to pervasive environmental problems often are not amenable to a straightforward application of science-based actions. These problems encompass large-scale environmental policy questions where environmental concerns, economic constraints, and societal values conflict ca...

Decision Analysis Techniques for Adult Learners: Application to Leadership

ERIC Educational Resources Information Center

Toosi, Farah

2017-01-01

Most decision analysis techniques are not taught at higher education institutions. Leaders, project managers and procurement agents in industry have strong technical knowledge, and it is crucial for them to apply this knowledge at the right time to make critical decisions. There are uncertainties, problems, and risks involved in business…

Assessing the Impact of Financial Aid Offers on Enrollment Decisions.

ERIC Educational Resources Information Center

Somers, Patricia A.; St. John, Edward P.

1993-01-01

A study tested a model for assessing the impact of financial aid offers on 2,558 accepted students' college enrollment decisions. The analysis demonstrates that financial aid strategies have a substantial influence on enrollment and the systematic analysis of student enrollment decisions can help institutional administrators refine their financing…

An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

NASA Astrophysics Data System (ADS)

Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

2017-12-01

For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Non-Small Cell Lung Cancer.

PubMed

Raju, G K; Gurumurthi, K; Domike, R; Kazandjian, D; Blumenthal, G; Pazdur, R; Woodcock, J

2016-12-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analyses. There is much interest in quantifying regulatory approaches to benefit and risk. In this work the use of a quantitative benefit-risk analysis was applied to regulatory decision-making about new drugs to treat advanced non-small cell lung cancer (NSCLC). Benefits and risks associated with 20 US Food and Drug Administration (FDA) decisions associated with a set of candidate treatments submitted between 2003 and 2015 were analyzed. For benefit analysis, the median overall survival (OS) was used where available. When not available, OS was estimated based on overall response rate (ORR) or progression-free survival (PFS). Risks were analyzed based on magnitude (or severity) of harm and likelihood of occurrence. Additionally, a sensitivity analysis was explored to demonstrate analysis of systematic uncertainty. FDA approval decision outcomes considered were found to be consistent with the benefit-risk logic. © 2016 American Society for Clinical Pharmacology and Therapeutics.

How Expert Pilots Think Cognitive Processes in Expert Decision Making

DTIC Science & Technology

1993-02-01

Management (CRM) This document is available to the public Advanced Qualification Program (AQP) through the National Technical Information Cognitive Task Analysis (CTA...8217 Selecting realistic EDM scenarios with critical events and performing a cognitive task analysis of novice vs. expert decision making for these events...scenarios with critical events and performing a cognitive task analysis of novice vs. expert decision making for these events is a basic requirement for

Multi-Metric Sustainability Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cowlin, Shannon; Heimiller, Donna; Macknick, Jordan

2014-12-01

A readily accessible framework that allows for evaluating impacts and comparing tradeoffs among factors in energy policy, expansion planning, and investment decision making is lacking. Recognizing this, the Joint Institute for Strategic Energy Analysis (JISEA) funded an exploration of multi-metric sustainability analysis (MMSA) to provide energy decision makers with a means to make more comprehensive comparisons of energy technologies. The resulting MMSA tool lets decision makers simultaneously compare technologies and potential deployment locations.

Toward an Extension of Decision Analysis to Competitive Situations.

DTIC Science & Technology

1985-12-01

order to deal with competition may ease the use of non- von Neumann-Morgenstern utility. This leads to our secondary goal of questioning expected...While von WInterfeldt [1980] attempted a 5 (more detailed analysis using three separate decision trees, one for each side In the dispute, he felt that...rationality generally used In game theory derives from the same roots as the calculated rationality of Decision Analysis, von Neumann and

How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide.

PubMed

Diaby, Vakaramoko; Goeree, Ron

2014-02-01

In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

Determining the Best Treatment for Coronal Angular Deformity of the Knee Joint in Growing Children: A Decision Analysis

PubMed Central

Sung, Ki Hyuk; Chung, Chin Youb; Lee, Kyoung Min; Lee, Seung Yeol; Choi, In Ho; Cho, Tae-Joon; Yoo, Won Joon; Park, Moon Seok

2014-01-01

This study aimed to determine the best treatment modality for coronal angular deformity of the knee joint in growing children using decision analysis. A decision tree was created to evaluate 3 treatment modalities for coronal angular deformity in growing children: temporary hemiepiphysiodesis using staples, percutaneous screws, or a tension band plate. A decision analysis model was constructed containing the final outcome score, probability of metal failure, and incomplete correction of deformity. The final outcome was defined as health-related quality of life and was used as a utility in the decision tree. The probabilities associated with each case were obtained by literature review, and health-related quality of life was evaluated by a questionnaire completed by 25 pediatric orthopedic experts. Our decision analysis model favored temporary hemiepiphysiodesis using a tension band plate over temporary hemiepiphysiodesis using percutaneous screws or stapling, with utilities of 0.969, 0.957, and 0.962, respectively. One-way sensitivity analysis showed that hemiepiphysiodesis using a tension band plate was better than temporary hemiepiphysiodesis using percutaneous screws, when the overall complication rate of hemiepiphysiodesis using a tension band plate was lower than 15.7%. Two-way sensitivity analysis showed that hemiepiphysiodesis using a tension band plate was more beneficial than temporary hemiepiphysiodesis using percutaneous screws. PMID:25276801

[Comparison of Discriminant Analysis and Decision Trees for the Detection of Subclinical Keratoconus].

PubMed

Kleinhans, Sonja; Herrmann, Eva; Kohnen, Thomas; Bühren, Jens

2017-08-15

Background Iatrogenic keratectasia is one of the most dreaded complications of refractive surgery. In most cases, keratectasia develops after refractive surgery of eyes suffering from subclinical stages of keratoconus with few or no signs. Unfortunately, there has been no reliable procedure for the early detection of keratoconus. In this study, we used binary decision trees (recursive partitioning) to assess their suitability for discrimination between normal eyes and eyes with subclinical keratoconus. Patients and Methods The method of decision tree analysis was compared with discriminant analysis which has shown good results in previous studies. Input data were 32 eyes of 32 patients with newly diagnosed keratoconus in the contralateral eye and preoperative data of 10 eyes of 5 patients with keratectasia after laser in-situ keratomileusis (LASIK). The control group was made up of 245 normal eyes after LASIK and 12-month follow-up without any signs of iatrogenic keratectasia. Results Decision trees gave better accuracy and specificity than did discriminant analysis. The sensitivity of decision trees was lower than the sensitivity of discriminant analysis. Conclusion On the basis of the patient population of this study, decision trees did not prove to be superior to linear discriminant analysis for the detection of subclinical keratoconus. Georg Thieme Verlag KG Stuttgart · New York.

Value of information analysis in healthcare: a review of principles and applications.

PubMed

Tuffaha, Haitham W; Gordon, Louisa G; Scuffham, Paul A

2014-06-01

Economic evaluations are increasingly utilized to inform decisions in healthcare; however, decisions remain uncertain when they are not based on adequate evidence. Value of information (VOI) analysis has been proposed as a systematic approach to measure decision uncertainty and assess whether there is sufficient evidence to support new technologies. The objective of this paper is to review the principles and applications of VOI analysis in healthcare. Relevant databases were systematically searched to identify VOI articles. The findings from the selected articles were summarized and narratively presented. Various VOI methods have been developed and applied to inform decision-making, optimally designing research studies and setting research priorities. However, the application of this approach in healthcare remains limited due to technical and policy challenges. There is a need to create more awareness about VOI analysis, simplify its current methods, and align them with the needs of decision-making organizations.

Joint Intelligence Analysis Complex: DOD Partially Used Best Practices for Analyzing Alternatives and Should Do So Fully for Future Military Construction Decisions

DTIC Science & Technology

2016-09-01

Military Construction Decisions Report to Congressional Requesters September 2016 GAO-16-853 United States Government Accountability Office...ANALYSIS COMPLEX DOD Partially Used Best Practices for Analyzing Alternatives and Should Do So Fully for Future Military Construction Decisions What...a set of AOA best practices for military construction decisions. Without guidance for using AOA best practices during certain military construction

Escalation research: Providing new frontiers for applying behavior analysis to organizational behavior

PubMed Central

Goltz, Sonia M.

2000-01-01

Decision fiascoes such as escalation of commitment, the tendency of decision makers to “throw good money after bad,” can have serious consequences for organizations and are therefore of great interest in applied research. This paper discusses the use of behavior analysis in organizational behavior research on escalation. Among the most significant aspects of behavior-analytic research on escalation is that it has indicated that both the patterns of outcomes that decision makers have experienced for past decisions and the patterns of responses that they make are critical for understanding escalation. This research has also stimulated the refinement of methods by researchers to better assess decision making and the role reinforcement plays in it. Finally, behavior-analytic escalation research has not only indicated the utility of reinforcement principles for predicting more complex human behavior but has also suggested some additional areas for future exploration of decision making using behavior analysis. PMID:22478347

Multi-criteria analysis for the detection of the most critical European UNESCO Heritage sites

NASA Astrophysics Data System (ADS)

Valagussa, Andrea; Frattini, Paolo; Berta, Nadia; Spizzichino, Daniele; Leoni, Gabriele; Margottini, Claudio; Battista Crosta, Giovanni

2017-04-01

A GIS-based multi-criteria analysis has been implemented to identify and to rank the most critical UNESCO Heritage sites at the European scale in the context of PROTHEGO JPI-Project. Two multi-criteria methods have been tested and applied to more than 300 European UNESCO Sites. First, the Analytic Hierarchy Procedure (AHP) was applied to the data of the UNESCO Periodic Report, in relation to 13 natural hazards that have affected or can potentially affect the Heritage sites. According to these reports, 22% of sites are without any documented hazard and 70% of the sites have at least one hazard affecting the site. The most important hazards on the European country are: fire (wildfire), storm, flooding, earthquake and erosion. For each UNESCO site, the potential risk was calculated as a weighed sum of the hazards that affect the site. The weighs of the 13 hazards were obtained by AHP procedure, which is a technique for multi-attribute decision making that enables the decomposition of a problem into hierarchy, based on the opinion of different experts about the dominance of risks. The weights are obtained by rescaling between 0 and 1 the eigenvectors relative to the maximum eigenvalue for the matrix of the coefficients. The internal coherence of the expert's attributions is defined through the calculation of the consistency ratio (Saaty, 1990). The result of the AHP method consists in a map of the UNESCO sites ranked according to the potential risk, where the site most at risk results to be the Geirangerfjord and Nærøyfjord in Norway. However, the quality of these results lies in the reliability of the Period Reports, which are produced by different experts with unknown level of scientific background. To test the reliability of these results, a comparison of the information of the periodic reports with available high-quality datasets (earthquake, volcano and landslide) at the Italian scale has been performed. Sites properly classified by the Period Reports range from 65% (earthquake hazard) to 98% (volcano hazard), with a high underestimation of landslide hazard. Due to this high value of uncertainty, we developed a new methodology to identify and to rank the most critical UNESCO Heritage sites on the basis of three natural hazards (landslide, earthquake, and volcano) for which reliable European-scale hazard maps are available. For each UNESCO site, a potential risk was calculated as the product of hazard (from the available maps) and potential vulnerability. The latter is obtained considering the typology of site (e.g. monument, cultural landscape, and cultural road), the presence or absence of resident and/or tourist, the position of the site (underground/over-ground). Through this methodology, a new ranking of the European UNESCO Sites has been obtained. In this ranking, the historic center of Naples results to be the most-at-danger site of the European continent.

Improving IT Portfolio Management Decision Confidence Using Multi-Criteria Decision Making and Hypervariate Display Techniques

ERIC Educational Resources Information Center

Landmesser, John Andrew

2014-01-01

Information technology (IT) investment decision makers are required to process large volumes of complex data. An existing body of knowledge relevant to IT portfolio management (PfM), decision analysis, visual comprehension of large volumes of information, and IT investment decision making suggest Multi-Criteria Decision Making (MCDM) and…

Modeling Adversaries in Counterterrorism Decisions Using Prospect Theory.

PubMed

Merrick, Jason R W; Leclerc, Philip

2016-04-01

Counterterrorism decisions have been an intense area of research in recent years. Both decision analysis and game theory have been used to model such decisions, and more recently approaches have been developed that combine the techniques of the two disciplines. However, each of these approaches assumes that the attacker is maximizing its utility. Experimental research shows that human beings do not make decisions by maximizing expected utility without aid, but instead deviate in specific ways such as loss aversion or likelihood insensitivity. In this article, we modify existing methods for counterterrorism decisions. We keep expected utility as the defender's paradigm to seek for the rational decision, but we use prospect theory to solve for the attacker's decision to descriptively model the attacker's loss aversion and likelihood insensitivity. We study the effects of this approach in a critical decision, whether to screen containers entering the United States for radioactive materials. We find that the defender's optimal decision is sensitive to the attacker's levels of loss aversion and likelihood insensitivity, meaning that understanding such descriptive decision effects is important in making such decisions. © 2014 Society for Risk Analysis.

Workshop on Aeronautical Decision Making (ADM). Volume 1. Executive Summary

DTIC Science & Technology

1992-08-01

expert and novice pilots when a real decision was required. Aeronautical Decision Making (ADM), Crew Resource Management (CRM), Advanced Qualification Program (AQP), Cognitive Task Analysis (CTA), Expert Decision Making (EDM)

Choices, choices: the application of multi-criteria decision analysis to a food safety decision-making problem.

PubMed

Fazil, A; Rajic, A; Sanchez, J; McEwen, S

2008-11-01

In the food safety arena, the decision-making process can be especially difficult. Decision makers are often faced with social and fiscal pressures when attempting to identify an appropriate balance among several choices. Concurrently, policy and decision makers in microbial food safety are under increasing pressure to demonstrate that their policies and decisions are made using transparent and accountable processes. In this article, we present a multi-criteria decision analysis approach that can be used to address the problem of trying to select a food safety intervention while balancing various criteria. Criteria that are important when selecting an intervention were determined, as a result of an expert consultation, to include effectiveness, cost, weight of evidence, and practicality associated with the interventions. The multi-criteria decision analysis approach we present is able to consider these criteria and arrive at a ranking of interventions. It can also provide a clear justification for the ranking as well as demonstrate to stakeholders, through a scenario analysis approach, how to potentially converge toward common ground. While this article focuses on the problem of selecting food safety interventions, the range of applications in the food safety arena is truly diverse and can be a significant tool in assisting decisions that need to be coherent, transparent, and justifiable. Most importantly, it is a significant contributor when there is a need to strike a fine balance between various potentially competing alternatives and/or stakeholder groups.

Application of Bayesian and cost benefit risk analysis in water resources management

NASA Astrophysics Data System (ADS)

Varouchakis, E. A.; Palogos, I.; Karatzas, G. P.

2016-03-01

Decision making is a significant tool in water resources management applications. This technical note approaches a decision dilemma that has not yet been considered for the water resources management of a watershed. A common cost-benefit analysis approach, which is novel in the risk analysis of hydrologic/hydraulic applications, and a Bayesian decision analysis are applied to aid the decision making on whether or not to construct a water reservoir for irrigation purposes. The alternative option examined is a scaled parabolic fine variation in terms of over-pumping violations in contrast to common practices that usually consider short-term fines. The methodological steps are analytically presented associated with originally developed code. Such an application, and in such detail, represents new feedback. The results indicate that the probability uncertainty is the driving issue that determines the optimal decision with each methodology, and depending on the unknown probability handling, each methodology may lead to a different optimal decision. Thus, the proposed tool can help decision makers to examine and compare different scenarios using two different approaches before making a decision considering the cost of a hydrologic/hydraulic project and the varied economic charges that water table limit violations can cause inside an audit interval. In contrast to practices that assess the effect of each proposed action separately considering only current knowledge of the examined issue, this tool aids decision making by considering prior information and the sampling distribution of future successful audits.

Structured decision making: Chapter 5

USGS Publications Warehouse

Runge, Michael C.; Grand, James B.; Mitchell, Michael S.; Krausman, Paul R.; Cain, James W. III

2013-01-01

Wildlife management is a decision-focused discipline. It needs to integrate traditional wildlife science and social science to identify actions that are most likely to achieve the array of desires society has surrounding wildlife populations. Decision science, a vast field with roots in economics, operations research, and psychology, offers a rich set of tools to help wildlife managers frame, decompose, analyze, and synthesize their decisions. The nature of wildlife management as a decision science has been recognized since the inception of the field, but formal methods of decision analysis have been underused. There is tremendous potential for wildlife management to grow further through the use of formal decision analysis. First, the wildlife science and human dimensions of wildlife disciplines can be readily integrated. Second, decisions can become more efficient. Third, decisions makers can communicate more clearly with stakeholders and the public. Fourth, good, intuitive wildlife managers, by explicitly examining how they make decisions, can translate their art into a science that is readily used by the next generation.

Benefit-Risk Analysis for Decision-Making: An Approach.

PubMed

Raju, G K; Gurumurthi, K; Domike, R

2016-12-01

The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.

Analyses of S-Box in Image Encryption Applications Based on Fuzzy Decision Making Criterion

NASA Astrophysics Data System (ADS)

Rehman, Inayatur; Shah, Tariq; Hussain, Iqtadar

2014-06-01

In this manuscript, we put forward a standard based on fuzzy decision making criterion to examine the current substitution boxes and study their strengths and weaknesses in order to decide their appropriateness in image encryption applications. The proposed standard utilizes the results of correlation analysis, entropy analysis, contrast analysis, homogeneity analysis, energy analysis, and mean of absolute deviation analysis. These analyses are applied to well-known substitution boxes. The outcome of these analyses are additional observed and a fuzzy soft set decision making criterion is used to decide the suitability of an S-box to image encryption applications.

Methods for Conducting Cognitive Task Analysis for a Decision Making Task.

DTIC Science & Technology

1996-01-01

Cognitive task analysis (CTA) improves traditional task analysis procedures by analyzing the thought processes of performers while they complete a...for using these methods to conduct a CTA for domains which involve critical decision making tasks in naturalistic settings. The cognitive task analysis methods

An Environmental Decision Support System for Spatial Assessment and Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates environmental assessment tools for effective problem-solving. The software integrates modules for GIS, visualization, geospatial analysis, statistical analysis, human health and ecolog...

Path Analysis Examining Self-Efficacy and Decision-Making Performance on a Simulated Baseball Task

ERIC Educational Resources Information Center

Hepler, Teri J.; Feltz, Deborah L.

2012-01-01

The purpose of this study was to examine the relationship between decision-making self-efficacy and decision-making performance in sport. Undergraduate students (N = 78) performed 10 trials of a decision-making task in baseball. Self-efficacy was measured before performing each trial. Decision-making performance was assessed by decision speed and…

Decision Styles and Rationality: An Analysis of the Predictive Validity of the General Decision-Making Style Inventory

ERIC Educational Resources Information Center

Curseu, Petru Lucian; Schruijer, Sandra G. L.

2012-01-01

This study investigates the relationship between the five decision-making styles evaluated by the General Decision-Making Style Inventory, indecisiveness, and rationality in decision making. Using a sample of 102 middle-level managers, the results show that the rational style positively predicts rationality in decision making and negatively…

Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

ERIC Educational Resources Information Center

Erskine, Michael A.

2013-01-01

As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…

Decision-Making Phenomena Described by Expert Nurses Working in Urban Community Health Settings.

ERIC Educational Resources Information Center

Watkins, Mary P.

1998-01-01

Expert community health nurses (n=28) described crucial clinical situations. Content analysis revealed that decision making was both rational and intuitive. Eight themes were identified: decision-making focus, type, purpose, decision-maker characteristics, sequencing of events, data collection methods, facilitators/barriers, and decision-making…

Patient participation in palliative care decisions: An ethnographic discourse analysis

PubMed Central

Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert

2016-01-01

The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize decisions that shaped patients’ dying trajectories. Discourse analysis encourages awareness of the role of language in either promoting or hindering patient participation in decision-making. PMID:27882864

Patient participation in palliative care decisions: An ethnographic discourse analysis.

PubMed

Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert

2016-01-01

The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize decisions that shaped patients' dying trajectories. Discourse analysis encourages awareness of the role of language in either promoting or hindering patient participation in decision-making.

Application of risk analysis in water resourses management

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil; Palogos, Ioannis

2017-04-01

A common cost-benefit analysis approach, which is novel in the risk analysis of hydrologic/hydraulic applications, and a Bayesian decision analysis are applied to aid the decision making on whether or not to construct a water reservoir for irrigation purposes. The alternative option examined is a scaled parabolic fine variation in terms of over-pumping violations in contrast to common practices that usually consider short-term fines. Such an application, and in such detail, represents new feedback. The results indicate that the probability uncertainty is the driving issue that determines the optimal decision with each methodology, and depending on the unknown probability handling, each methodology may lead to a different optimal decision. Thus, the proposed tool can help decision makers (stakeholders) to examine and compare different scenarios using two different approaches before making a decision considering the cost of a hydrologic/hydraulic project and the varied economic charges that water table limit violations can cause inside an audit interval. In contrast to practices that assess the effect of each proposed action separately considering only current knowledge of the examined issue, this tool aids decision making by considering prior information and the sampling distribution of future successful audits. This tool is developed in a web service for the easier stakeholders' access.

Shaping Strategy: An Institutional Analysis of Decision Making in the Middle Tier

ERIC Educational Resources Information Center

Vasquez, Alejandro

2017-01-01

The intent of this single-case study was to explore the effects of a competitive environment on organizational decision making. The study examines the decision making processes that resulted in the adoption of an undergraduate business major at a traditional, middle-tier Liberal Arts College and offers an analysis of academic leaders' perspectives…

EPA Growing DASEES (Decision Analysis For A Sustainable Environment, Economy & Society) - To Aid In Making Decisions On Complex Environmental Issues

EPA Science Inventory

Having a framework and tools to help sort through complicated environmental issues in an objective way would be useful to communities and risk managers, and all the stakeholders affected by these issues. This is one need that DASEES (Decision Analysis for a Sustainable En...

Decision modeling for fire incident analysis

Treesearch

Donald G. MacGregor; Armando González-Cabán

2009-01-01

This paper reports on methods for representing and modeling fire incidents based on concepts and models from the decision and risk sciences. A set of modeling techniques are used to characterize key fire management decision processes and provide a basis for incident analysis. The results of these methods can be used to provide insights into the structure of fire...

ALTERNATIVE FUTURES ANALYSIS: A FRAMEWORK FOR COMMUNITY DECISION-MAKING

EPA Science Inventory

Alternative futures analysis is an assessment approach designed to inform community decisions about land and water use. We conducted an alternative futures analysis in Oregon's Willamette River Basin. Three alternative future landscapes for the year 2050 were depicted and compare...

The Effects of Ecoregion Dynamics on Agroregions for Permanent Crops in the Continental US Under Future Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Maddalena, D. M.; L'Heureux, J.; Hoffman, F. M.

2017-12-01

Fruit and Tree Nut production in the US averaged 14% of total annual production, or roughly $28 billion in total revenue for the most recent 5 year period (2011 - 2015). The success of these crops is highly dependent on environmental conditions. Cold snaps before winter dormancy, early frosts in spring, and lack of sufficient chilling hours can reduce productivity, inflict wood damage, and lead to economic loss. Climate change can increase the likelihood of these threats and may have long-term implications for the areas where these crops are grown due to the migration of ecoregions as climate patters shift. We delineate ecoregions using multi-attribute spatio-temporal clustering and calculate chilling unit accumulation under past, present, and future climate scenarios using measured and modeled data. These results are then compared to current agroregions in the US to calculate risk dynamics, potential economic loss, and to map future agroregion scenarios. Our results offer considerations for food system sustainability under a shifting climate.

Visualizing multiattribute Web transactions using a freeze technique

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Cotting, Daniel; Dayal, Umeshwar; Machiraju, Vijay; Garg, Pankaj

2003-05-01

Web transactions are multidimensional and have a number of attributes: client, URL, response times, and numbers of messages. One of the key questions is how to simultaneously lay out in a graph the multiple relationships, such as the relationships between the web client response times and URLs in a web access application. In this paper, we describe a freeze technique to enhance a physics-based visualization system for web transactions. The idea is to freeze one set of objects before laying out the next set of objects during the construction of the graph. As a result, we substantially reduce the force computation time. This technique consists of three steps: automated classification, a freeze operation, and a graph layout. These three steps are iterated until the final graph is generated. This iterated-freeze technique has been prototyped in several e-service applications at Hewlett Packard Laboratories. It has been used to visually analyze large volumes of service and sales transactions at online web sites.

Hydrofutures and Hydromorphology

NASA Astrophysics Data System (ADS)

Lall, U.

2006-12-01

Hydromorphology refers to the science of hydrologic evolution. It represents a synthesis of planetary and social sciences that collectively determine the spatial and temporal evolution of planetary water. At present human actions directly or indirectly play a major role in determining hydrofutures. Man's role in changing water trajectories is now clear at both local and planetary scales. Changing climate leads to changing ecology and changing water patterns. Changing water conditions may in turn regulate (limit anthropogenic climate change) or adversely impact (e.g., runaway greenhouse) climate, as well as human habitation and water use patterns. This talk will address the problem of the prediction of future hydrologic conditions in the different media and reservoirs of the planet, from the integrated perspective indicated above. Key examples of the mechanisms of hydrologic change, that relate to climate and ecological dyanmics, and to human activity are identified as well. A theoretical framework for researching this multi-attribute dynamical system from a water centric perspective is advocated as a critical need for planetary science and human welfare.

Feature Integration in the Mapping of Multi-Attribute Visual Stimuli to Responses

PubMed Central

Ishizaki, Takuya; Morita, Hiromi; Morita, Masahiko

2015-01-01

In the human visual system, different attributes of an object, such as shape and color, are separately processed in different modules and then integrated to elicit a specific response. In this process, different attributes are thought to be temporarily “bound” together by focusing attention on the object; however, how such binding contributes to stimulus-response mapping remains unclear. Here we report that learning and performance of stimulus-response tasks was more difficult when three attributes of the stimulus determined the correct response than when two attributes did. We also found that spatially separated presentations of attributes considerably complicated the task, although they did not markedly affect target detection. These results are consistent with a paired-attribute model in which bound feature pairs, rather than object representations, are associated with responses by learning. This suggests that attention does not bind three or more attributes into a unitary object representation, and long-term learning is required for their integration. PMID:25762010

Structure Based Drug Design of Crizotinib (PF-02341066), a Potent and Selective Dual Inhibitor of Mesenchymal-Epithelial Transition Factor (c-MET) Kinase and Anaplastic Lymphoma Kinase (ALK)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, J Jean; Tran-Dube,; #769

2011-08-03

Because of the critical roles of aberrant signaling in cancer, both c-MET and ALK receptor tyrosine kinases are attractive oncology targets for therapeutic intervention. The cocrystal structure of 3 (PHA-665752), bound to c-MET kinase domain, revealed a novel ATP site environment, which served as the target to guide parallel, multiattribute drug design. A novel 2-amino-5-aryl-3-benzyloxypyridine series was created to more effectively make the key interactions achieved with 3. In the novel series, the 2-aminopyridine core allowed a 3-benzyloxy group to reach into the same pocket as the 2,6-dichlorophenyl group of 3 via a more direct vector and thus with amore » better ligand efficiency (LE). Further optimization of the lead series generated the clinical candidate crizotinib (PF-02341066), which demonstrated potent in vitro and in vivo c-MET kinase and ALK inhibition, effective tumor growth inhibition, and good pharmaceutical properties.« less

An evaluation of multiple trauma severity indices created by different index development strategies.

PubMed

Gustafson, D H; Fryback, D G; Rose, J H; Prokop, C T; Detmer, D E; Rossmeissl, J C; Taylor, C M; Alemi, F; Carnazzo, A J

1983-07-01

Evaluation of the effectiveness of emergency trauma care systems is complicated by the need to adjust for the widely variable case mix found in trauma patient populations. Several strategies have been advanced to construct the severity indices that can control for these population differences. This article describes a validity and reliability comparison of trauma severity indices developed under three different approaches: 1) use of a multi-attribute utility (MAU) model; 2) an actuarial approach relying on empirical data bases; and 3) an "ad hoc" approach. Seven criteria were identified to serve as standards of comparison for four different indices. The study's findings indicate that the index developed using the MAU theory approach associates most closely with physician judgments of trauma severity. When correlated with a morbidity outcome measure, the MAU-based index shows higher levels of agreement than the other indices. The index development approach based on the principles of MAU theory has several advantages and it appears to be a powerful tool in the creation of effective severity indices.

End-of-Life Decision Making in Palliative Care and Recommendations of the Council of Europe: Qualitative Secondary Analysis of Interviews and Observation Field Notes.

PubMed

Martins Pereira, Sandra; Fradique, Emília; Hernández-Marrero, Pablo

2018-05-01

End-of-life decisions (ELDs) are embedded in clinical, sociocultural, political, economic, and ethical concerns. In 2014, the Council of Europe (CoE) through its Committee on Bioethics launched the "Guide on the decision-making process regarding medical treatment in end-of-life situations," aiming at improving decision-making processes and empowering professionals in making ELDs. To analyze if end-of-life decision making in palliative care (PC) is consistent with this Guide and to identify if disputed/controversial issues are part of current ELDs. Qualitative secondary analysis. Four qualitative datasets, including 44 interviews and 9 team observation field notes from previous studies with PC teams/professionals in Portugal. An analysis grid based on the abovementioned guide was created considering three dimensions: ethical and legal frameworks, decision-making process, and disputed/controversial issues. The majority of the professionals considered the ethical principle of autonomy paramount in end-of-life decision making. Justice and beneficence/nonmaleficence were also valued. Although not mentioned in the Guide, the professionals also considered other ethical principles when making ELDs, namely, responsibility, integrity, and dignity. Most of the interviewees and field notes referred to the collective interprofessional dimension of the decision-making process. Palliative sedation and the wish to hasten death were the most mentioned disputed/controversial issues. The nature, limitations, and benefits of qualitative secondary analysis are discussed. End-of-life decision-making processes made by Portuguese PC teams seem to be consistent with the guidelines of the CoE. Further research is needed about disputed/controversial issues and the actual use, effectiveness, and impact of ethical guidelines for end-of-life decision making on professionals' empowerment and for all parties involved.

The BCD of response time analysis in experimental economics.

PubMed

Spiliopoulos, Leonidas; Ortmann, Andreas

2018-01-01

For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.

Using Cluster Analysis to Examine Husband-Wife Decision Making

ERIC Educational Resources Information Center

Bonds-Raacke, Jennifer M.

2006-01-01

Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

Development of Decision Making in School-Aged Children and Adolescents: Evidence from Heart Rate and Skin Conductance Analysis

ERIC Educational Resources Information Center

Crone, Eveline A.; van der Molen, Maurits W.

2007-01-01

Age differences in decision making indicate that children fail to anticipate outcomes of their decisions. Using heart rate and skin conductance analyses, we tested whether developmental changes in decision making are associated with (a) a failure to process outcomes of decisions, or (b) a failure to anticipate future outcomes of decisions.…

Levonorgestrel intrauterine system versus medical therapy for menorrhagia.

PubMed

Gupta, Janesh; Kai, Joe; Middleton, Lee; Pattison, Helen; Gray, Richard; Daniels, Jane

2013-01-10

Menorrhagia is a common problem, yet evidence to inform decisions about therapy is limited. In a pragmatic, multicenter, randomized trial, we compared the levonorgestrel-releasing intrauterine system (levonorgestrel-IUS) with usual medical treatment in women with menorrhagia who presented to their primary care providers. We randomly assigned 571 women with menorrhagia to treatment with levonorgestrel-IUS or usual medical treatment (tranexamic acid, mefenamic acid, combined estrogen-progestogen, or progesterone alone). The primary outcome was the patient-reported score on the Menorrhagia Multi-Attribute Scale (MMAS) (ranging from 0 to 100, with lower scores indicating greater severity), assessed over a 2-year period. Secondary outcomes included general quality-of-life and sexual-activity scores and surgical intervention. MMAS scores improved from baseline to 6 months in both the levonorgestrel-IUS group and the usual-treatment group (mean increase, 32.7 and 21.4 points, respectively; P<0.001 for both comparisons). The improvements were maintained over a 2-year period but were significantly greater in the levonorgestrel-IUS group than in the usual-treatment group (mean between-group difference, 13.4 points; 95% confidence interval, 9.9 to 16.9; P<0.001). Improvements in all MMAS domains (practical difficulties, social life, family life, work and daily routine, psychological well-being, and physical health) were significantly greater in the levonorgestrel-IUS group than in the usual-treatment group, and this was also true for seven of the eight quality-of-life domains. At 2 years, more of the women were still using the levonorgestrel-IUS than were undergoing the usual medical treatment (64% vs. 38%, P<0.001). There were no significant between-group differences in the rates of surgical intervention or sexual-activity scores. There were no significant differences in serious adverse events between groups. In women with menorrhagia who presented to primary care providers, the levonorgestrel-IUS was more effective than usual medical treatment in reducing the effect of heavy menstrual bleeding on quality of life. (Funded by the National Institute of Health Research Health Technology Assessment Programme; ECLIPSE Controlled-Trials.com number, ISRCTN86566246.).

Parents' versus physicians' values for clinical outcomes in young febrile children.

PubMed

Kramer, M S; Etezadi-Amoli, J; Ciampi, A; Tange, S M; Drummond, K N; Mills, E L; Bernstein, M L; Leduc, D G

1994-05-01

To compare how parents and physicians value potential clinical outcomes in young children who have a fever but no focus of bacterial infection. Cross-sectional study of 100 parents of well children aged 3 to 24 months, 61 parents of febrile children aged 3 to 24 months, and 56 attending staff physicians working in a children's hospital emergency department. A pretested visual analog scale was used to assess values on a 0-to-1 scale (where 0 is the value of the worst possible outcome, and 1 is the value for the best) for 22 scenarios, grouped in three categories according to severity. Based on the three or four common attributes comprising the scenarios in a given group, each respondent's value function was estimated statistically based on multiattribute utility theory. For outcomes in group 1 (rapidly resolving viral infection with one or more diagnostic tests), no significant group differences were observed. For outcomes in groups 2 (acute infections without long-term sequelae) and 3 (long-term sequelae of urinary tract infection or bacterial meningitis), parents of well children and parents of febrile children had values that were similar to each other but significantly lower than physicians' values for pneumonia with delayed diagnosis, false-positive diagnosis of urinary tract infection, viral meningitis, and unilateral hearing loss. For bacterial meningitis with or without delay, however, the reverse pattern was observed; physicians' values were lower than parents'. In arriving at their judgment for group 2 and 3 scenarios, parents gave significantly greater weight to attributes involving the pain and discomfort of diagnostic tests and to diagnostic error, whereas physicians gave significantly greater weight to attributes involving both short- and long-term morbidity and long-term worry and inconvenience. Parents were significantly more likely to be risk-seeking in the way they weighted the attributes comprising group 2 and 3 scenarios than physicians, ie, they were more willing to risk rare but severe morbidity to avoid the short-term adverse effects of testing. Parents and physicians show fundamental value differences concerning diagnostic testing, diagnostic error, and short- and long-term morbidity; these differences have important implications for diagnostic decision making in the young febrile child.

Contribution of the Multi-attribute Value Theory to conflict resolution in groundwater management. Application to the Mancha Oriental system (Spain)

NASA Astrophysics Data System (ADS)

Apperl, B.; Pulido-Velazquez, M.; Andreu, J.; Llopis-Albert, C.

2012-04-01

The implementation of the EU Water Framework Directive, with consideration of environmental, economic and social objectives, claims for participatory water resource management methods. To deal with different conflicting objectives it is necessary to apply a method for clarifying stakeholders' positions (identifying values and opinions of stakeholders, and quantifying their valuations), improving transparency with respect to outcomes of alternatives, and moving the discussion from alternatives towards fundamental objectives (value-thinking approach) and valuing trade-offs, facilitating negotiation. The method allows the incorporation of stakeholders in the planning process, which should guarantee a higher acceptance of the policies to be implemented. This research has been conducted in the Mancha Oriental groundwater system Spain, subject to an intensive use of groundwater for irrigation. The main goals according to the WFD are: a good qualitative and quantitative status of the aquifer and a good quantitative and ecological status of related surface water resources (mainly the Jucar river and dependent ecosystems). The aim is to analyze the contribution of the MAVT for conflict resolution and a sustainable groundwater management, involving the stakeholders in the valuation process. A complex set of objectives and attributes has been defined. The alternatives have been evaluated according to the compliance of ecological, economic and social interests. Results show that the acceptation of alternatives depends strongly on the combination of measures and the implementation status. A high conflict potential is expected from alternatives consisting of one unique measure. Uncertainties of the results are notable, but do not influence heavily on the alternative ranking. Different future scenarios also influence on the preference of alternatives. For instance, an expected reduction of future groundwater resources by climate change increases the conflict potential, with two observed reactions: acceptance of more rigorous measures, on one hand, and a tendency to soft measures with the same cost, as a reaction to the decreased effectiveness of the alternatives. The implementation of the method to a very complex case study, with many conflicting objectives and alternatives and uncertain outcomes, including future scenarios (climate change) illustrate the potential of the method for supporting management decisions.

The application of decision analysis to life support research and technology development

NASA Technical Reports Server (NTRS)

Ballin, Mark G.

1994-01-01

Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.

Using Decision Analysis to Improve Malaria Control Policy Making

PubMed Central

Kramer, Randall; Dickinson, Katherine L.; Anderson, Richard M.; Fowler, Vance G.; Miranda, Marie Lynn; Mutero, Clifford M.; Saterson, Kathryn A.; Wiener, Jonathan B.

2013-01-01

Malaria and other vector-borne diseases represent a significant and growing burden in many tropical countries. Successfully addressing these threats will require policies that expand access to and use of existing control methods, such as insecticide-treated bed nets and artemesinin combination therapies for malaria, while weighing the costs and benefits of alternative approaches over time. This paper argues that decision analysis provides a valuable framework for formulating such policies and combating the emergence and re-emergence of malaria and other diseases. We outline five challenges that policy makers and practitioners face in the struggle against malaria, and demonstrate how decision analysis can help to address and overcome these challenges. A prototype decision analysis framework for malaria control in Tanzania is presented, highlighting the key components that a decision support tool should include. Developing and applying such a framework can promote stronger and more effective linkages between research and policy, ultimately helping to reduce the burden of malaria and other vector-borne diseases. PMID:19356821

A framework for sensitivity analysis of decision trees.

PubMed

Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław

2018-01-01

In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.

Risk analysis theory applied to fishing operations: A new approach on the decision-making problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cunha, J.C.S.

1994-12-31

In the past the decisions concerning whether to continue or interrupt a fishing operation were based primarily on the operator`s previous experience. This procedure often led to wrong decisions and unnecessary loss of money and time. This paper describes a decision-making method based on risk analysis theory and previous operation results from a field under study. The method leads to more accurate decisions on a daily basis allowing the operator to verify each day of the operation if the decision being carried out is the one with the highest probability to conduct to the best economical result. An example ofmore » the method application is provided at the end of the paper.« less

Analysis And Assistant Planning System Ofregional Agricultural Economic Inform

NASA Astrophysics Data System (ADS)

Han, Jie; Zhang, Junfeng

For the common problems existed in regional development and planning, we try to design a decision support system for assisting regional agricultural development and alignment as a decision-making tool for local government and decision maker. The analysis methods of forecast, comparative advantage, liner programming and statistical analysis are adopted. According to comparative advantage theory, the regional advantage can be determined by calculating and comparing yield advantage index (YAI), Scale advantage index (SAI), Complicated advantage index (CAI). Combining with GIS, agricultural data are presented as a form of graph such as area, bar and pie to uncover the principle and trend for decision-making which can't be found in data table. This system provides assistant decisions for agricultural structure adjustment, agro-forestry development and planning, and can be integrated to information technologies such as RS, AI and so on.

Factors influencing decision regret regarding placement of a PEG among substitute decision-makers of older persons in Japan: a prospective study.

PubMed

Kuraoka, Yumiko; Nakayama, Kazuhiro

2017-06-28

A tube feeding decision aid designed at the Ottawa Health Research Institute was specifically created for substitute decision-makers who must decide whether to allow placement of a percutaneous endoscopic gastrostomy (PEG) tube in a cognitively impaired older person. We developed a Japanese version and found that the decision aid promoted the decision-making process of substitute decision-makers to decrease decisional conflict and increase knowledge. However, the factors that influence decision regret among substitute decision-makers were not measured after the decision was made. The objective of this study was to explore the factors that influence decision regret among substitute decision-makers 6 months after using a decision aid for PEG placement. In this prospective study, participants comprised substitute decision-makers for 45 inpatients aged 65 years and older who were being considered for placement of a PEG tube in hospitals, nursing homes and patients' homes in Japan. The Decisional Conflict Scale (DCS) was used to evaluate decisional conflict among substitute decision-makers immediately after deciding whether to introduce tube feeding and the Decision Regret Scale (DRS) was used to evaluate decisional regret among substitute decision-makers 6 months after they made their decision. Normalized scores were evaluated and analysis of variance was used to compare groups. The results of the multiple regression analysis suggest that PEG placement (P < .01) and decision conflict (P < .001) are explanatory factors of decision regret regarding placement of a PEG among substitute decision-makers. PEG placement and decision conflict immediately after deciding whether to allow PEG placement have an influence on decision regret among substitute decision-makers after 6 months.

The use of decision analysis to evaluate the economic effects of heat mount detectors in two dairy herds.

PubMed

Williamson, N B

1975-03-01

This paper reports a decrease in the interval from calving to conception in two commercial dairy herds, associated with the use of KaMaR Heat Mount Detectors. An economic analysis of the results uses a neoclassical decision theory approach to demonstrate that the use of heat mount detectors is likely to be profitable, with an expected net return of $154.18 per 100 calvings. The analysis demonstrates the suitability of a decision-theoretic approach to the analysis of applied research, and illustrates some of the weaknesses of "Classical" statistical analysis in such circumstances.

Decision strategies to reduce teenage and young adult deaths in the United States.

PubMed

Keeney, Ralph L; Palley, Asa B

2013-09-01

This article uses decision analysis concepts and techniques to address an extremely important problem to any family with children, namely, how to avoid the tragic death of a child during the high-risk ages of 15-24. Descriptively, our analysis indicates that of the 35,000 annual deaths among this age group in the United States, approximately 20,000 could be avoided if individuals chose readily available alternatives for decisions relating to these deaths. Prescriptively, we develop a decision framework for parents and a child to both identify and proactively pursue decisions that can lower that child's exposure to life-threatening risks and positively alter decisions when facing such risks. Applying this framework for parents and the youth themselves, we illustrate the logic and process of generating proactive alternatives with numerous examples that each could pursue to lower these life-threatening risks and possibly avoid a tragic premature death, and discuss some public policy implications of our findings. © 2013 Society for Risk Analysis.

Conceptualizing Surrogate Decision-Making at End of Life in the Intensive Care Unit using Cognitive Task Analysis

PubMed Central

Dionne-Odom, J. Nicholas; Willis, Danny G.; Bakitas, Marie; Crandall, Beth; Grace, Pamela J.

2014-01-01

Background Surrogate decision-makers (SDMs) face difficult decisions at end of life (EOL) for decisionally incapacitated intensive care unit (ICU) patients. Purpose Identify and describe the underlying psychological processes of surrogate decision-making for adults at EOL in the ICU. Method Qualitative case study design using a cognitive task analysis (CTA) interviewing approach. Participants were recruited from October 2012 to June 2013 from an academic tertiary medical center’s ICU located in the rural Northeastern United States. Nineteen SDMs for patients who had died in the ICU completed in-depth semi-structured CTA interviews. Discussion The conceptual framework formulated from data analysis reveals that three underlying, iterative, psychological dimensions: gist impressions, distressing emotions, and moral intuitions impact a SDM’s judgment about the acceptability of either the patient’s medical treatments or his or her condition. Conclusion The framework offers initial insights about the underlying psychological processes of surrogate decision-making and may facilitate enhanced decision support for SDMs. PMID:25982772

Neural systems analysis of decision making during goal-directed navigation.

PubMed

Penner, Marsha R; Mizumori, Sheri J Y

2012-01-01

The ability to make adaptive decisions during goal-directed navigation is a fundamental and highly evolved behavior that requires continual coordination of perceptions, learning and memory processes, and the planning of behaviors. Here, a neurobiological account for such coordination is provided by integrating current literatures on spatial context analysis and decision-making. This integration includes discussions of our current understanding of the role of the hippocampal system in experience-dependent navigation, how hippocampal information comes to impact midbrain and striatal decision making systems, and finally the role of the striatum in the implementation of behaviors based on recent decisions. These discussions extend across cellular to neural systems levels of analysis. Not only are key findings described, but also fundamental organizing principles within and across neural systems, as well as between neural systems functions and behavior, are emphasized. It is suggested that studying decision making during goal-directed navigation is a powerful model for studying interactive brain systems and their mediation of complex behaviors. Copyright © 2011. Published by Elsevier Ltd.

Defining the optimal therapy sequence in synchronous resectable liver metastases from colorectal cancer: a decision analysis approach.

PubMed

Van Dessel, E; Fierens, K; Pattyn, P; Van Nieuwenhove, Y; Berrevoet, F; Troisi, R; Ceelen, W

2009-01-01

Approximately 5%-20% of colorectal cancer (CRC) patients present with synchronous potentially resectable liver metastatic disease. Preclinical and clinical studies suggest a benefit of the 'liver first' approach, i.e. resection of the liver metastasis followed by resection of the primary tumour. A formal decision analysis may support a rational choice between several therapy options. Survival and morbidity data were retrieved from relevant clinical studies identified by a Web of Science search. Data were entered into decision analysis software (TreeAge Pro 2009, Williamstown, MA, USA). Transition probabilities including the risk of death from complications or disease progression associated with individual therapy options were entered into the model. Sensitivity analysis was performed to evaluate the model's validity under a variety of assumptions. The result of the decision analysis confirms the superiority of the 'liver first' approach. Sensitivity analysis demonstrated that this assumption is valid on condition that the mortality associated with the hepatectomy first is < 4.5%, and that the mortality of colectomy performed after hepatectomy is < 3.2%. The results of this decision analysis suggest that, in patients with synchronous resectable colorectal liver metastases, the 'liver first' approach is to be preferred. Randomized trials will be needed to confirm the results of this simulation based outcome.

The decision tree classifier - Design and potential. [for Landsat-1 data

NASA Technical Reports Server (NTRS)

Hauska, H.; Swain, P. H.

1975-01-01

A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

The application of natural science data to land management decision-making

NASA Technical Reports Server (NTRS)

Williams, D. L.; Sharpe, C. P.; Rowe, P. G.

1974-01-01

A natural environmental analysis process which allows the decision maker to know the probable consequences of a decision prior to the act is developed. Emphasis is placed on the fit between the natural environment and the social, economic, and functional attributes of man's communities and the transition from nature in its present state to various forms and intensities of development. Applications of the analysis are examined. It is concluded that the analysis is a workable system for land use management.

Decision Analysis in the U.S. Army’s Capabilties Needs Analysis: Applications of Decision Analysis Methods to Capabilities Resource Allocation and Capabilities Development Decisions

DTIC Science & Technology

2015-10-01

capability to meet the task to the standard under the condition, nothing more or less, else the funding is wasted . Also, that funding for the...bin to segregate gaps qualitatively before the gap value model determined preference among gaps within the bins. Computation of a gap’s...for communication, interpretation, or processing by humans or by automatic means (as it pertains to modeling and simulation). Delphi Method -- a

Decisions, decisions: analysis of age, cohort, and time of testing on framing of risky decision options.

PubMed

Mayhorn, Christopher B; Fisk, Arthur D; Whittle, Justin D

2002-01-01

Decision making in uncertain environments is a daily challenge faced by adults of all ages. Framing decision options as either gains or losses is a common method of altering decision-making behavior. In the experiment reported here, benchmark decision-making data collected in the 1970s by Tversky and Kahneman (1981, 1988) were compared with data collected from current samples of young and older adults to determine whether behavior was consistent across time. Although differences did emerge between the benchmark and the present samples, the effect of framing on decision behavior was relatively stable. The present findings suggest that adults of all ages are susceptible to framing effects. Results also indicated that apparent age differences might be better explained by an analysis of cohort and time-of-testing effects. Actual or potential applications of this research include an understanding of how framing might influence the decision-making behavior of people of all ages in a number of applied contexts, such as product warning interactions and medical decision scenarios.

Comparative Analysis of Enrollment and Financial Strength of Private Institutions. AIR 1989 Annual Forum Paper.

ERIC Educational Resources Information Center

Glover, Robert H.; Mills, Michael R.

A research design, decision support system, and results of a comparative analysis of enrollment and financial strength (of private institutions granting masters and doctoral degrees) are presented. Cluster analysis, discriminant analysis, multiple regression, and an interactive decision support system are used to compare the enrollment and…

Decision analysis in formulary decision making.

PubMed

Schechter, C B

1993-06-01

Although decision making about what drugs to include in an institutional formulary appears to lend itself readily to quantitative techniques such as decision analysis and cost-benefit analysis, a review of the literature reveals that very little has been published in this area. Several of the published decision analyses use non-standard techniques that are, at best, of unproved validity, and may seriously distort the underlying issues through covert under-counting or double-counting of various drug attributes. Well executed decision analyses have contributed to establishing that drug acquisition costs are not an adequate measure of the total economic impact of formulary decisions and that costs of labour and materials associated with drug administration must be calculated on an institution-specific basis to reflect unique staffing patterns, bulk purchasing practices, and the availability of surplus capacity within the institution which might be mobilised at little marginal cost. Clinical studies of newly introduced drugs frequently fail to answer the questions that weigh most heavily on the structuring of a formal assessment of a proposed formulary acquisition. Studies comparing a full spectrum of therapeutically equivalent drugs are rarely done, and individual studies of particular pairs of drugs can rarely be used together because of differences in methodology or patient populations studied. Gathering of institution-specific economic and clinical data is a daunting, labour-intensive task. In many institutions, incentive and reward structures discourage behaviour that takes the broad institutional perspective that is intrinsic to a good decision analysis.(ABSTRACT TRUNCATED AT 250 WORDS)

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

Decision analysis applied to the purchase of frozen premixed intravenous admixtures.

PubMed

Witte, K W; Eck, T A; Vogel, D P

1985-04-01

A structured decision-analysis model was used to evaluate frozen premixed cefazolin admixtures. Decision analysis is a process of stating the desired outcome, establishing and weighting evaluation criteria, identifying options for reaching the outcome, evaluating and numerically ranking each option for each criterion, multiplying the ranking by the weight for each criterion, and calculating total points for each option. It was used to compare objectively frozen premixed cefazolin admixtures with batch reconstitution from vials and reconstitution of lyophilized, ready-to-mix containers. In this institution the model numerically demonstrated a distinct preference for the premixed frozen admixture over these other alternatives. A comparison of these results with the total cost impact of each option resulted in a decision to purchase the frozen premixed solution. The advantages of the frozen premixed solution that contributed most to this decision were decreased waste and personnel time. The latter was especially important since it allowed for the reallocation of personnel resources to other potentially cost-reducing clinical functions. Decision analysis proved to be an effective tool for formalizing the process of selecting among various alternatives to reach a desired outcome in this hospital pharmacy.

Using the Situated Clinical Decision-Making framework to guide analysis of nurses' clinical decision-making.

PubMed

Gillespie, Mary

2010-11-01

Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.

Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA.

PubMed

Mühlbacher, Axel C; Kaczynski, Anika

2016-02-01

Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

Accuracy of intuition in clinical decision-making among novice clinicians.

PubMed

Price, Amanda; Zulkosky, Kristen; White, Krista; Pretz, Jean

2017-05-01

To assess the reliance on intuitive and analytical approaches during clinical decision-making among novice clinicians and whether that reliance is associated with accurate decision-making. Nurse educators and managers tend to emphasize analysis over intuition during clinical decision-making though nurses typically report some reliance on intuition in their practice. We hypothesized that under certain conditions, reliance on intuition would support accurate decision-making, even among novices. This study utilized an experimental design with clinical complication (familiar vs. novel) and decision phase (cue acquisition, diagnosis and action) as within-subjects' factors, and simulation role (observer, family, auxiliary nurse and primary nurse) as between-subjects' factor. We examined clinical decision-making accuracy among final semester pre-licensure nursing students in a simulation experience. Students recorded their reasoning about emerging clinical complications with their patient during two distinct points in the simulation; one point involved a familiar complication and the other a relatively novel complication. All data were collected during Spring 2015. Although most participants relied more heavily on analysis than on intuition, use of intuition during the familiar complication was associated with more accurate decision-making, particularly in guiding attention to relevant cues. With the novel complication, use of intuition appeared to hamper decision-making, particularly for those in an observer role. Novice clinicians should be supported by educators and nurse managers to note when their intuitions are likely to be valid. Our findings emphasize the integrated nature of intuition and analysis in clinical decision-making. © 2016 John Wiley & Sons Ltd.

My Lived Experiences Are More Important Than Your Probabilities: The Role of Individualized Risk Estimates for Decision Making about Participation in the Study of Tamoxifen and Raloxifene (STAR).

PubMed

Holmberg, Christine; Waters, Erika A; Whitehouse, Katie; Daly, Mary; McCaskill-Stevens, Worta

2015-11-01

Decision-making experts emphasize that understanding and using probabilistic information are important for making informed decisions about medical treatments involving complex risk-benefit tradeoffs. Yet empirical research demonstrates that individuals may not use probabilities when making decisions. To explore decision making and the use of probabilities for decision making from the perspective of women who were risk-eligible to enroll in the Study of Tamoxifen and Raloxifene (STAR). We conducted narrative interviews with 20 women who agreed to participate in STAR and 20 women who declined. The project was based on a narrative approach. Analysis included the development of summaries of each narrative, and thematic analysis with developing a coding scheme inductively to code all transcripts to identify emerging themes. Interviewees explained and embedded their STAR decisions within experiences encountered throughout their lives. Such lived experiences included but were not limited to breast cancer family history, a personal history of breast biopsies, and experiences or assumptions about taking tamoxifen or medicines more generally. Women's explanations of their decisions about participating in a breast cancer chemoprevention trial were more complex than decision strategies that rely solely on a quantitative risk-benefit analysis of probabilities derived from populations In addition to precise risk information, clinicians and risk communicators should recognize the importance and legitimacy of lived experience in individual decision making. © The Author(s) 2015.

MAT - MULTI-ATTRIBUTE TASK BATTERY FOR HUMAN OPERATOR WORKLOAD AND STRATEGIC BEHAVIOR RESEARCH

NASA Technical Reports Server (NTRS)

Comstock, J. R.

1994-01-01

MAT, a Multi-Attribute Task battery, gives the researcher the capability of performing multi-task workload and performance experiments. The battery provides a benchmark set of tasks for use in a wide range of laboratory studies of operator performance and workload. MAT incorporates tasks analogous to activities that aircraft crew members perform in flight, while providing a high degree of experiment control, performance data on each subtask, and freedom to use non-pilot test subjects. The MAT battery primary display is composed of four separate task windows which are as follows: a monitoring task window which includes gauges and warning lights, a tracking task window for the demands of manual control, a communication task window to simulate air traffic control communications, and a resource management task window which permits maintaining target levels on a fuel management task. In addition, a scheduling task window gives the researcher information about future task demands. The battery also provides the option of manual or automated control of tasks. The task generates performance data for each subtask. The task battery may be paused and onscreen workload rating scales presented to the subject. The MAT battery was designed to use a serially linked second computer to generate the voice messages for the Communications task. The MATREMX program and support files, which are included in the MAT package, were designed to work with the Heath Voice Card (Model HV-2000, available through the Heath Company, Benton Harbor, Michigan 49022); however, the MATREMX program and support files may easily be modified to work with other voice synthesizer or digitizer cards. The MAT battery task computer may also be used independent of the voice computer if no computer synthesized voice messages are desired or if some other method of presenting auditory messages is devised. MAT is written in QuickBasic and assembly language for IBM PC series and compatible computers running MS-DOS. The code in MAT is written for Microsoft QuickBasic 4.5 and Microsoft Macro Assembler 5.1. This package requires a joystick and EGA or VGA color graphics. An 80286, 386, or 486 processor machine is highly recommended. The standard distribution medium for MAT is a 5.25 inch 360K MS-DOS format diskette. The files are compressed using the PKZIP file compression utility. PKUNZIP is included on the distribution diskette. MAT was developed in 1992. IBM PC is a registered trademark of International Business Machines. MS-DOS, Microsoft QuickBasic, and Microsoft Macro Assembler are registered trademarks of Microsoft Corporation. PKZIP and PKUNZIP are registered trademarks of PKWare, Inc.

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

Thompson, David R.

2011-01-01

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

A pilot level decision analysis of thermionic reactor development strategy for nuclear electric propulsion

NASA Technical Reports Server (NTRS)

Menke, M. M.; Judd, B. R.

1973-01-01

The development policy for thermionic reactors to provide electric propulsion and power for space exploration was analyzed to develop a logical procedure for selecting development alternatives that reflect the technical feasibility, JPL/NASA project objectives, and the economic environment of the project. The partial evolution of a decision model from the underlying philosophy of decision analysis to a deterministic pilot phase is presented, and the general manner in which this decision model can be employed to examine propulsion development alternatives is illustrated.

Decision Analysis for Multicandidate Voting Systems. Applications of Elementary Decision Analysis to Political Science. [and] An Application of Voting Theory to Congress. Applications of Decision Theory and Game Theory to American Politics. Modules and Monographs in Undergraduate Mathematics and Its Applications Project. UMAP Units 384 and 386.

ERIC Educational Resources Information Center

Merrill, Samuel, III; Enelow, James M.

This document consists of two modules. The first studies a variety of multicandidate voting systems, including approval, Borda, and cumulative voting, using a model which takes account of a voter's intensity of preference for candidates. The voter's optimal strategy is investigated for each voting system using decision criteria under uncertainty…

The role of risk-based prioritization in total quality management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bennett, C.T.

1994-10-01

The climate in which government managers must make decisions grows more complex and uncertain. All stakeholders - the public, industry, and Congress - are demanding greater consciousness, responsibility, and accountability of programs and their budgets. Yet, managerial decisions have become multifaceted, involve greater risk, and operate over much longer time periods. Over the last four or five decades, as policy analysis and decisions became more complex, scientists from psychology, operations research, systems science, and economics have developed a more or less coherent process called decision analysis to aid program management. The process of decision analysis - a systems theoretic approachmore » - provides the backdrop for this paper. The Laboratory Integrated Prioritization System (LIPS) has been developed as a systems analytic and risk-based prioritization tool to aid the management of the Tri-Labs` (Lawrence Livermore, Los Alamos, and Sandia) operating resources. Preliminary analyses of the effects of LIPS has confirmed the practical benefits of decision and systems sciences - the systematic, quantitative reduction in uncertainty. To date, the use of LIPS - and, hence, its value - has been restricted to resource allocation within the Tri-Labs` operations budgets. This report extends the role of risk-based prioritization to the support of DOE Total Quality Management (TQM) programs. Furthermore, this paper will argue for the requirement to institutionalize an evolutionary, decision theoretic approach to the policy analysis of the Department of Energy`s Program Budget.« less

The Process of Life Cycle Cost Analysis: Projecting Economic Consequences of Design Decisions

ERIC Educational Resources Information Center

AIA Journal, 1976

1976-01-01

Life-cycle cost analysis deals with both present and future costs and attempts to relate the two as a basis for making decisions. This article lays the groundwork for a better understanding of the techniques of life-cycle cost analysis. (Author/MLF)

75 FR 58374 - 2010 Release of CADDIS (Causal Analysis/Diagnosis Decision Information System)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-24

... 2010 version of the Causal Analysis/Diagnosis Decision Information System (CADDIS). This Web site was... methods; information on basic and advanced data analyses; downloadable software tools; and an online... ENVIRONMENTAL PROTECTION AGENCY [FRL-9206-7] 2010 Release of CADDIS (Causal Analysis/Diagnosis...

Decision analysis of shoreline protection under climate change uncertainty

NASA Astrophysics Data System (ADS)

Chao, Philip T.; Hobbs, Benjamin F.

1997-04-01

If global warming occurs, it could significantly affect water resource distribution and availability. Yet it is unclear whether the prospect of such change is relevant to water resources management decisions being made today. We model a shoreline protection decision problem with a stochastic dynamic program (SDP) to determine whether consideration of the possibility of climate change would alter the decision. Three questions are addressed with the SDP: (l) How important is climate change compared to other uncertainties?, (2) What is the economic loss if climate change uncertainty is ignored?, and (3) How does belief in climate change affect the timing of the decision? In the case study, sensitivity analysis shows that uncertainty in real discount rates has a stronger effect upon the decision than belief in climate change. Nevertheless, a strong belief in climate change makes the shoreline protection project less attractive and often alters the decision to build it.

Leadership Style, Decision Context, and the Poliheuristic Theory of Decision Making: An Experimental Analysis

ERIC Educational Resources Information Center

Keller, Jonathan W.; Yang, Yi Edward

2008-01-01

The poliheuristic (PH) theory of decision making has made important contributions to our understanding of political decision making but remains silent about certain key aspects of the decision process. Specifically, PH theory contends that leaders screen out politically unacceptable options, but it provides no guidance on (1) the crucial threshold…

Why, When, and How to Take into Account the Uncertainty Involved in Career Decisions.

ERIC Educational Resources Information Center

Gati, Itamar

1990-01-01

Theoretically analyzes career decisions under uncertainty, when career decision maker ranks options rather than choosing best one. Found that how decisions were framed affected ranking of options and quality of decisions. Analysis showed that the rank order of options in optimal ranking always coincided with the rank order of the options by their…

Patient and provider perceptions of decision making about use of epidural analgesia during childbirth: a thematic analysis.

PubMed

Goldberg, Holly Bianca; Shorten, Allison

2014-01-01

This study examines the nature of differences in perceptions of decision making between patients and providers about use of epidural analgesia during labor. Thematic analysis was used to identify patterns in written survey responses from 14 patients, 13 labor nurses, and 7 obstetrician-gynecologists. Results revealed patients attempted to place themselves in an informed role in decision making and sought respect for their decisions. Some providers demonstrated paternalism and a tendency to steer patients in the direction of their own preferences. Nurses observed various pressures on decision making, reinforcing the importance of patients being supported to make an informed choice. Differences in perceptions suggest need for improvement in communication and shared decision-making practices related to epidural analgesia use in labor.

Decision-making impairments in Parkinson's disease as a by-product of defective cost-benefit analysis and feedback processing.

PubMed

Ryterska, Agata; Jahanshahi, Marjan; Osman, Magda

2014-01-01

Studies examining decision-making in people with Parkinson's disease (PD) show impaired performance on a variety of tasks. However, there are also demonstrations that patients with PD can make optimal decisions just like healthy age-matched controls. We propose that the reason for these mixed findings is that PD does not produce a generalized impairment of decision-making, but rather affects sub-components of this process. In this review we evaluate this hypothesis by considering the empirical evidence examining decision-making in PD. We suggest that of the various stages of the decision-making process, the most affected in PD are (1) the cost-benefit analysis stage and (2) the outcome evaluation stage. We consider the implications of this proposal for research in this area.

When do cancer patients regret their treatment decision? A path analysis of the influence of clinicians' communication styles and the match of decision-making styles on decision regret.

PubMed

Nicolai, Jennifer; Buchholz, Angela; Seefried, Nathalie; Reuter, Katrin; Härter, Martin; Eich, Wolfgang; Bieber, Christiane

2016-05-01

To test the influence of physician empathy (PE), shared decision making (SDM), and the match between patients' preferred and perceived decision-making styles on patients' decision regret. Patients with breast or colon cancer (n=71) completed questionnaires immediately following (T1) and three months after a consultation (T2). Path analysis was used to examine the relationships among patient demographics, patient reports of PE, SDM, the match between preferred and perceived decision-making styles, and patient decision regret at T2. After controlling for clinician clusters, higher PE was directly associated with more SDM (β=0.43, p<0.01) and lower decision regret (β=-0.28, p<0.01). The match between patients' preferred and perceived roles was negatively associated with decision regret (β=-0.33, p<0.01). Patients who participated less than desired reported more decision regret at T2. There was no significant association between SDM and decision regret (β=0.03, p=0.74). PE and the match between patients' preferred and perceived roles in medical decision making are essential for patient-centered cancer consultations and treatment decisions. Ways to enhance PE and matching the consultation style to patients' expectations should be encouraged. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Human-computer interface for the study of information fusion concepts in situation analysis and command decision support systems

NASA Astrophysics Data System (ADS)

Roy, Jean; Breton, Richard; Paradis, Stephane

2001-08-01

Situation Awareness (SAW) is essential for commanders to conduct decision-making (DM) activities. Situation Analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision maker. Operational trends in warfare put the situation analysis process under pressure. This emphasizes the need for a real-time computer-based Situation analysis Support System (SASS) to aid commanders in achieving the appropriate situation awareness, thereby supporting their response to actual or anticipated threats. Data fusion is clearly a key enabler for SA and a SASS. Since data fusion is used for SA in support of dynamic human decision-making, the exploration of the SA concepts and the design of data fusion techniques must take into account human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight integration of the human element with the SA technology is essential. Regarding these issues, this paper provides a description of CODSI (Command Decision Support Interface), and operational- like human machine interface prototype for investigations in computer-based SA and command decision support. With CODSI, one objective was to apply recent developments in SA theory and information display technology to the problem of enhancing SAW quality. It thus provides a capability to adequately convey tactical information to command decision makers. It also supports the study of human-computer interactions for SA, and methodologies for SAW measurement.

Robustness Regions for Dichotomous Decisions.

ERIC Educational Resources Information Center

Vijn, Pieter; Molenaar, Ivo W.

1981-01-01

In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)

Dynamics of individual perceptual decisions

PubMed Central

Clark, Torin K.; Lu, Yue M.; Karmali, Faisal

2015-01-01

Perceptual decision making is fundamental to a broad range of fields including neurophysiology, economics, medicine, advertising, law, etc. Although recent findings have yielded major advances in our understanding of perceptual decision making, decision making as a function of time and frequency (i.e., decision-making dynamics) is not well understood. To limit the review length, we focus most of this review on human findings. Animal findings, which are extensively reviewed elsewhere, are included when beneficial or necessary. We attempt to put these various findings and data sets, which can appear to be unrelated in the absence of a formal dynamic analysis, into context using published models. Specifically, by adding appropriate dynamic mechanisms (e.g., high-pass filters) to existing models, it appears that a number of otherwise seemingly disparate findings from the literature might be explained. One hypothesis that arises through this dynamic analysis is that decision making includes phasic (high pass) neural mechanisms, an evidence accumulator and/or some sort of midtrial decision-making mechanism (e.g., peak detector and/or decision boundary). PMID:26467513

The Potential for Meta-Analysis to Support Decision Analysis in Ecology

ERIC Educational Resources Information Center

Mengersen, Kerrie; MacNeil, M. Aaron; Caley, M. Julian

2015-01-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…

Documentation of Decision-Aiding Software: Introductory Guide

DTIC Science & Technology

1980-02-01

for the Manager ( New York: Holt, ’ 6 ( Simply put, the discipline assists planners and deci- sion makers in choosing between alternative courses of...con- ducting international negotiations on tanker safety; g. use by Headquarters, U.S. Marine Corps as an orga- nizing vehicle for the preparation of...literature on decision analysis. For an introductory treatment the reader should refer to Howard Raiffa, Decision Analysis (Reading, Massachusetts

Signal Detection Analysis of Computer Enhanced Group Decision Making Strategies

DTIC Science & Technology

2007-11-01

group decision making. 20 References American Psychological Association (2002). Ethical principles of psychologists and code of conduct. American... Creelman , C. D. (2005). Detection theory: A user’s guide (2nd ed.). Mahwah, NJ: Lawrence Erlbaum. Sorkin, R. D. (1998). Group performance depends on...the majority rule. Psychological Science, 9, 456-463. Sorkin, R. D. (2001). Signal-detection analysis of group decision making. Psychological

The impact of management science on political decision making

NASA Technical Reports Server (NTRS)

White, M. J.

1971-01-01

The possible impact on public policy and organizational decision making of operations research/management science (OR/MS) is discussed. Criticisms based on the assumption that OR/MS will have influence on decision making and criticisms based on the assumption that it will have no influence are described. New directions in the analysis of analysis and in thinking about policy making are also considered.

Safety Assessment of Dangerous Goods Transport Enterprise Based on the Relative Entropy Aggregation in Group Decision Making Model

PubMed Central

Wu, Jun; Li, Chengbing; Huo, Yueying

2014-01-01

Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises. PMID:25477954

Safety assessment of dangerous goods transport enterprise based on the relative entropy aggregation in group decision making model.

PubMed

Wu, Jun; Li, Chengbing; Huo, Yueying

2014-01-01

Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises.

Decision-problem state analysis methodology

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

A methodology for analyzing a decision-problem state is presented. The methodology is based on the analysis of an incident in terms of the set of decision-problem conditions encountered. By decomposing the events that preceded an unwanted outcome, such as an accident, into the set of decision-problem conditions that were resolved, a more comprehensive understanding is possible. All human-error accidents are not caused by faulty decision-problem resolutions, but it appears to be one of the major areas of accidents cited in the literature. A three-phase methodology is presented which accommodates a wide spectrum of events. It allows for a systems content analysis of the available data to establish: (1) the resolutions made, (2) alternatives not considered, (3) resolutions missed, and (4) possible conditions not considered. The product is a map of the decision-problem conditions that were encountered as well as a projected, assumed set of conditions that should have been considered. The application of this methodology introduces a systematic approach to decomposing the events that transpired prior to the accident. The initial emphasis is on decision and problem resolution. The technique allows for a standardized method of accident into a scenario which may used for review or the development of a training simulation.

Real options analysis for land use management: Methods, application, and implications for policy.

PubMed

Regan, Courtney M; Bryan, Brett A; Connor, Jeffery D; Meyer, Wayne S; Ostendorf, Bertram; Zhu, Zili; Bao, Chenming

2015-09-15

Discounted cash flow analysis, including net present value is an established way to value land use and management investments which accounts for the time-value of money. However, it provides a static view and assumes passive commitment to an investment strategy when real world land use and management investment decisions are characterised by uncertainty, irreversibility, change, and adaptation. Real options analysis has been proposed as a better valuation method under uncertainty and where the opportunity exists to delay investment decisions, pending more information. We briefly review the use of discounted cash flow methods in land use and management and discuss their benefits and limitations. We then provide an overview of real options analysis, describe the main analytical methods, and summarize its application to land use investment decisions. Real options analysis is largely underutilized in evaluating land use decisions, despite uncertainty in policy and economic drivers, the irreversibility and sunk costs involved. New simulation methods offer the potential for overcoming current technical challenges to implementation as demonstrated with a real options simulation model used to evaluate an agricultural land use decision in South Australia. We conclude that considering option values in future policy design will provide a more realistic assessment of landholder investment decision making and provide insights for improved policy performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Uncertainty

USGS Publications Warehouse

Hunt, Randall J.

2012-01-01

Management decisions will often be directly informed by model predictions. However, we now know there can be no expectation of a single ‘true’ model; thus, model results are uncertain. Understandable reporting of underlying uncertainty provides necessary context to decision-makers, as model results are used for management decisions. This, in turn, forms a mechanism by which groundwater models inform a risk-management framework because uncertainty around a prediction provides the basis for estimating the probability or likelihood of some event occurring. Given that the consequences of management decisions vary, it follows that the extent of and resources devoted to an uncertainty analysis may depend on the consequences. For events with low impact, a qualitative, limited uncertainty analysis may be sufficient for informing a decision. For events with a high impact, on the other hand, the risks might be better assessed and associated decisions made using a more robust and comprehensive uncertainty analysis. The purpose of this chapter is to provide guidance on uncertainty analysis through discussion of concepts and approaches, which can vary from heuristic (i.e. the modeller’s assessment of prediction uncertainty based on trial and error and experience) to a comprehensive, sophisticated, statistics-based uncertainty analysis. Most of the material presented here is taken from Doherty et al. (2010) if not otherwise cited. Although the treatment here is necessarily brief, the reader can find citations for the source material and additional references within this chapter.

Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis.

PubMed

Lo, Benjamin W Y; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H

2016-01-01

Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56-2.45, P < 0.01). A clinically useful classification tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.

Decision analysis with cumulative prospect theory.

PubMed

Bayoumi, A M; Redelmeier, D A

2000-01-01

Individuals sometimes express preferences that do not follow expected utility theory. Cumulative prospect theory adjusts for some phenomena by using decision weights rather than probabilities when analyzing a decision tree. The authors examined how probability transformations from cumulative prospect theory might alter a decision analysis of a prophylactic therapy in AIDS, eliciting utilities from patients with HIV infection (n = 75) and calculating expected outcomes using an established Markov model. They next focused on transformations of three sets of probabilities: 1) the probabilities used in calculating standard-gamble utility scores; 2) the probabilities of being in discrete Markov states; 3) the probabilities of transitioning between Markov states. The same prophylaxis strategy yielded the highest quality-adjusted survival under all transformations. For the average patient, prophylaxis appeared relatively less advantageous when standard-gamble utilities were transformed. Prophylaxis appeared relatively more advantageous when state probabilities were transformed and relatively less advantageous when transition probabilities were transformed. Transforming standard-gamble and transition probabilities simultaneously decreased the gain from prophylaxis by almost half. Sensitivity analysis indicated that even near-linear probability weighting transformations could substantially alter quality-adjusted survival estimates. The magnitude of benefit estimated in a decision-analytic model can change significantly after using cumulative prospect theory. Incorporating cumulative prospect theory into decision analysis can provide a form of sensitivity analysis and may help describe when people deviate from expected utility theory.