Robustness Regions for Dichotomous Decisions

Vijn, Pieter; Molenaar, Ivo W.

doi:10.2307/1164874

Cited by 6 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They contradict current knowledge and prescriptions for generating scenarios to craft management strategies for complex social-ecological systems fraught with uncertainty that increases with the length of horizon considered (e.g., Cox, 2012;Comes et al, 2013;Matrosov et al, 2013;Ram and Montibeller, 2013). Vijn and Molenaar (1981) proposed that "The total set of all such assumptions/specifications for which the decision would have been the same is the robustness region." The assumptions behind the scenarios did not have a robustness region for the project decisions.…”

Section: What If We Grow and Don't Do Things Differently?mentioning

confidence: 99%

“…Matrosov et al (2013) proposed that "a robust decision works satisfactorily over a broad range of possible futures." The realization that robustness is necessary is not recent (e.g., Vijn and Molenaar, 1981;Ben-Haim, 2000). It has gained added currency with respect to the uncertainty of climate change consequences predicted for specific locations (e.g., Comes et al, 2013).…”

Section: Governance In Legacy Citiesmentioning

confidence: 99%

See 1 more Smart Citation

Governance for (climate) change in American “Legacy” cities: a case study of Cleveland

Kaufman

2016

Climate Adaptation Governance in Cities and Regions

View full text Add to dashboard Cite

Section: What If We Grow and Don't Do Things Differently?mentioning

confidence: 99%

Section: Governance In Legacy Citiesmentioning

confidence: 99%

Governance for (climate) change in American “Legacy” cities: a case study of Cleveland

Kaufman

2016

Climate Adaptation Governance in Cities and Regions

View full text Add to dashboard Cite

“…With respect to losses, a robustness study can be performed in order to find out to what extent uncertainty might be harmful with respect to the value of the losses. De Gmijter (1980) and Vijn and Molenaar (1981) have proposed robustness studies where the loss ratio and the standard no are jointly varied. However, research on the choice and robustness of loss functions is only beginning.…”

Section: University Of Massachusetts Amherstmentioning

confidence: 99%

On de Encountered Using Decision Theory to Set Cutoff Scores

Gruijter¹,

Hambleton

1984

Applied Psychological Measurement

View full text Add to dashboard Cite

In the decision-theoretic approach to determining a cutoff score, the cutoff score chosen is that which maximizes expected utility of pass/fail decisions. This approach is not without its problems. In this paper several of these problems are considered: inaccurate parameter estimates, choice of test model and consequences, choice of subpopulations, optimal cutoff scores on various occasions, and cutoff scores as targets. It is suggested that these problems will need to be overcome and/or understood more thoroughly before the full potential of the decision-theoretic approach can be realized in practice.The decision-theoretic paradigm for setting cutoff scores with criterion-referenced tests works in the following manner. In making mastery decisions on the basis of criterion-referenced test scores, two kinds of errors can result: passing examinees who are true nonmasters and failing examinees who are true masters (Hambleton, Swaminathan, Algina, & Coulson, 1978). A loss function is attached to the two types of errors, and then a cutoff score is chosen to maximize expected utility or to minimize expected loss with the available examinee test data.Among the researchers who have described the use of decision theory for setting cutoff scores are Hambleton and Novick (1973), Huynh (1976), Van der Linden and Mellenbergh (1977), and Van der Linden (1980). e Despite the conceptual appeal of the approach to some researchers, 9 the approach appears to have a number of problems at the implementation stage which have not been thoroughly discussed in the psychometric literature, with the significant exception of a recent paper by Glass (1978). In fact, an inadequate cutoff score can arise through the use of decision theory because of these problems. To dante, these problems have not been encountered or discussed to any extent, perhaps because of the few actual applications of decision theory for setting cutoff scores. Still, in view of the apparent attractiveness of the approach and the number of advocates for the approach in the criterion-referenced testing literature, it is not unreasonable to expect an increase in the number of applications in the future. The purpose of this paper is to discuss five problems that arise when decision theory is used to set cutoff scores. The basic paradigm for setting optimal cutoff scores will be reviewed in the first section of this paper. In the subsequent sections, five problems with the decision-theoretic paradigm are discussed.Despite the problems with decision-theoretic procedures that will be considered in this paper, it may be that these procedures are the most appropriate to use in some situations. It should be emphasized that it is not the author intention to compare decision-theoretic procedures for setting standards with other available methods nor to suggest that the five problems are unique to decisionat The University of Iowa Libraries on May 31, 2015 apm.sagepub.com Downloaded from

show abstract

Normal Approximations to Some Discrete Distributions

Molenaar¹

2014

Wiley StatsRef: Statistics Reference Online

View full text Add to dashboard Cite

Robustness Regions for Dichotomous Decisions

Cited by 6 publications

References 0 publications

Governance for (climate) change in American “Legacy” cities: a case study of Cleveland

Governance for (climate) change in American “Legacy” cities: a case study of Cleveland

On de Encountered Using Decision Theory to Set Cutoff Scores

Normal Approximations to Some Discrete Distributions

Contact Info

Product

Resources

About