Selecting a best multiattribute alternative with partial information about attribute weights

Use of approximate weights would greatly simplify decision analysis under certainty since detailed weight elicitation could be avoided. This paper examines the degree to which rank order information about weights can be used to identify a best alternative, or falling uniqueness prescribes an easily implemented rule for selecting a ‘best’ alternative. The prescribed rule uses as weights the centroid of the feasible region defined by the rank order information. In conjunction with the rule, the value of the rank order information can be determined using an ‘expected gain from weight precision’ (EGWP) measure, analogous to ‘expected value of perfect information’ in decision analysis under uncertainty.     

Everyday memory performance across the life span: effects of age and noncognitive individual differences.

Gerontologists have long been concerned with the impact of individual-difference factors on memory. This study used a large sample (N = 2,495) of adult volunteers aged 18 to 90 years to determine if a set of individual-difference variables--vocabulary, education, depression, gender, marital status, and employment status--mediates the effects of aging on a wide range of laboratory-analogue tests of everyday memory. The data indicated that age was consistently the most significant predictor of memory performance, followed by vocabulary and gender. Vocabulary totally mediated age effects on a prose memory measure, and partial mediation of aging effects--primarily by vocabulary and gender--was observed on 5 other memory tests. These data suggest that when health samples of volunteers serve as research subjects, these individual differences can affect some memory test scores, but age remains the best overall predictor of memory performance.     

New perspectives on child and adolescent depression

The Children's Depression Index (CDI) was administered to a group of 304 regular school students in Grades 3–12. It was found that 21% of the students reported mild to moderate levels and 7% reported severe levels of depression. Females reported more overall depression than did males. Specific CDI items selected more frequently by females than by males supports previous work suggesting that females tend to internalize difficulties whereas males are more likely to externalize problems. There were no age differences associated with overall depression; however, there were some developmental differences in specific items cited. Finally, “red flags” were identified that may be helpful in spotting children suffering from severe levels of depression.     

Differences that suggest female investment in,and male distance from,children

A factorial between subjects experiment was conducted with sex of respondent, level of success, sex of stimulus parent, and sex of stimulus child as the independent variables. Two hundred seventy-two undergraduates without parenting experience constituted the sample. The attributions made to explain parenting success/failure and the ratings made both of the child and the parent on the same 60 personality item were the dependent variables. Female respondents were not only especially success-oriented, but evidenced a view of parenting emphasizing deliberation and skill, whereas their male counterparts were comparatively more inclined to explain failure in terms of it being the child's fault and to overstate a child's meanness.This investigation was completed on the first author's NIMH traineeship (5 T01 MH-14473) for doctoral study. The authors are appreciative of the contributions of Professors Donn Byrne, Kay Deaux, and William Martin to the development of this study.     

Resource-Allocation Behavior in Complex but Commonplace Tasks

We all face resource-allocation tasks, yet little is known about how people make resource-allocation decisions. Three earlier papers (Langholtz, Gettys, & Foote, 1993, 1994, 1995) established that people can intuitively solve technical two-dimensional resource-allocation problems, where allocations are made on a continuous scale, reaching solutions that approach the optimum solution determined with Linear Programming (LP). In this research we expand our understanding of how people make resource-allocation decisions by examining how people perform complex but commonplace problems using a discrete scale where optimal solutions are determined with Integer Programming. We also contrast performance under conditions where progressively unequal scheduling is required to reach the optimum solution. The data show people can achieve solutions that provide most of the payoffs found with LP, even when they are faced with a complicated three-dimensional problem, but there is a tendency toward equal scheduling under all conditions.     

Axiomatic and numerical conjoint measurement: An evaluation of diagnostic efficacy

Synthetic data are used to examine how well axiomatic and numerical conjoint measurement methods, individually and comparatively, recover simple polynomial generators in three dimensions. The study illustrates extensions of numerical conjoint measurement (NCM) to identify and model distributive and dual-distributive, in addition to the usual additive, data structures. It was found that while minimum STRESS was the criterion of fit, another statistic, predictive capability, provided a better diagnosis of the known generating model. That NCM methods were able to better identify generating models conflicts with Krantz and Tversky's assertion that, in general, the direct axiom tests provide a more powerful diagnostic test between alternative composition rules than does evaluation of numerical correspondence. For all methods, dual-distributive models are most difficult to recover, while consistent with past studies, the additive model is the most robust of the fitted models.Douglas Emery is now at the Krannert Graduate School of Management, Purdue University, West Lafayette, IN, on leave from the University of Calgary.