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Trade-Offs Depend on Attribute Range

Profile image of Barbara MellersBarbara Mellers

Abstract

Contextual effects due to attribute range were examined in single-attribute and multiattribute judgments. The effect of a given attribute difference was greater when presented in a narrow range than a wide range. Stretching and shrinking the range of attributes altered the rank orders of judgments assigned to the same stimuli in different ranges. Trade-offs between time and money, one measure of ability and another, and achievement and motivation depended on attribute range. Although changes in trade-offs can result from changes in weights, data were consistent with the hypothesis that attribute range influences scale values. Scale values for common levels of an attribute spanned a wider interval when the attribute range was narrow than when the attribute range was wide.

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References (57)

  1. Beattie, J., & Baron, J. (1991). Investigating the effect of stimulus range on attribute weight. Journal of Experimental Psychology: Human Perception and Performance, 17, 571-585.
  2. Birnbaum, M. H. (1974a). The nonadditivity of personality im- pressions. Journal of Experimental Psychology, 102, 543-561.
  3. Birnbaum, M. H. (1974b). Reply to the Devil's advocates: Don't confound model testing and measurement. Psychological Bulle- tin, 81, 854-859.
  4. Birnbaum, M. H. (1976). Intuitive numerical prediction. American Journal of Psychology, 89, 417-429.
  5. Birnbaum, M. H. (1980). A recipe for weights and scales in multiattribute judgment. Unpublished manuscript.
  6. Birnbaum, M. H., Coffey, G., Mellers, B. A., & Weiss, R. (1992). Utility measurement: Configural-weight theory and the judge's point of view. Journal of Experimental Psychology: Human Perception and Performance, 18, 337-346.
  7. Birnbaum, M. H., & Mellers, B. A. (1983). Bayesian inference: Combining base rates with opinions of sources who vary in credibility. Journal of Personality and Social Psychology, 45, 792-804.
  8. Birnbaum, M. H., & Stegner, S. E. (1979). Source credibility in social judgment: Bias, expertise, and the judge's point of view. Journal of Personality and Social Psychology, 37, 48-74.
  9. Birnbaum, M. H., & Stegner, S. E. (1981). Measuring the impor- tance of cues in judgment for individuals: Subjective theories of IQ as a function of heredity and environment. Journal of Ex- perimental Social Psychology, 17, 159-182.
  10. Birnbaum, M. H., & Sutton, S. E. (1992). Scale convergence and utility measurement. Organizational Behavior and Human De- cision Processes, 17, 159-182.
  11. Birnbaum, M. H., Wong, R., & Wong, L. (1976). Combining information from sources that vary in credibility. Memory & Cognition, 4, 330-336.
  12. Chandler, J. (1969). STEPIT: Finds local minima of a smooth function of several parameters. Behavioral Science, 14, 81-82.
  13. Cooke, A., & Mellers, B. A. (1994). Attribute range and response range in multiattribute judgment. Unpublished manuscript.
  14. Fischer, G. W. (1991). Range sensitivity of attribute weights in multiattribute utility assessment. Unpublished manuscript, Duke University, Center for Decision Studies, Fuqua School of Busi- ness, Durham, NC.
  15. Fiske, S. T. (1980). Attention and weight in person perception: The impact of negative and extreme information. Journal of Person- ality and Social Psychology, 38, 889-906.
  16. Frank, R. H. (1991). Microeconomics and behavior. New York: McGraw-Hill.
  17. Gabrielli, W. F., & von Winterfeldt, D. (1978). Are attribute weights sensitive to the range of attribute values in multiat- tribute utility measurement? Unpublished manuscript.
  18. Goldstein, W. M. (1990). Judgments of relative importance in decision making: Global vs. local interpretations of subjective weight. Organizational Behavior and Human Decision Pro- cesses, 47, 313-336.
  19. Goldstein, W. M., & Einhorn, H. (1987). Expression theory and the preference reversal phenomenon. Psychological Review, 94, 236-254.
  20. Gravetter, F. (1971). Stimulus range as a frame of reference for judgment. Unpublished doctoral dissertation, Duke University.
  21. Gravetter, F., & Lockhead, G. R. (1973). Critical range as a frame of reference for stimulus judgment. Psychological Review, 80, 203-216.
  22. Grether, D. M., & Plott, C. R. (1979). Economic theory of choice and the preference reversal phenomenon. American Economic Review, 69, 623-638.
  23. Hershey, J. C., & Schoemaker, P. (1980). Risk taking and problem context in the domain of losses: An expected utility analysis. Journal of Risk and Insurance, 47, 111-132.
  24. Holland, M. K. (1968). Channel capacity and sequential effects: The influence of the immediate stimulus history on recogni- tion performance. Unpublished doctoral dissertation, Duke University.
  25. Hutchinson, J. W. (1983). On the locus of range effects in judg- ment and choice. In R. P. Bagozzi & A. M. Tybout (Eds.), Advances in consumer research (Vol. 10, pp. 305-308). Ann Arbor, MI: Association for Consumer Research.
  26. Kahneman, D., & Tversky, A. (1984). Choices, values, and frames. American Psychologist, 39, 341-350.
  27. Kaplan, M. F. (1971). Dispositional effects and weight of infor- mation in impression formation. Journal of Personality and Social Psychology, 18, 279-284.
  28. Levin, I. P., Kim, K. J., & Corey, F. A. (1976). Invariance of the weight parameter in information integration. Memory & Cogni- tion, 4, 43-47.
  29. Lynch, J. G., Chakravarti, D., & Mitra, A. (1991). Contrast effects in consumer judgments: Changes in mental representations or in the anchoring of rating scales. Journal of Consumer Re- search, 18, 284-297.
  30. Massaro, D., & Friedman, D. (1990). Models of integration given multiple sources of information. Psychological Review, 97, 226-252.
  31. McNeil, B. J., Pauker, S. G., Sox, H. C., Jr., & Tversky, A. (1982). On the elicitation of preferences for alternative therapies. New England Journal of Medicine, 306, 1259-1262.
  32. Mellers, B. A. (1982). Equity judgment: A revision of Aristotelian views. Journal of Experimental Psychology: General, 111, 242-270.
  33. Mellers, B. A., & Birnbaum, M. H. (1982). Loci of contextual effects in judgment. Journal of Experimental Psychology: Hu- man Perception and Performance, 8, 582-601.
  34. Mellers, B. A., & Birnbaum, M. H. (1983). Contextual effects in social judgment. Journal of Experimental Social Psychology, 19, 157-171.
  35. Mellers, B. A., Chang, S., Birnbaum, M. H., & Ordonez, L. D. (1992). Preferences, prices, and ratings in risky decision making.
  36. • Journal of Experimental Psychology: Human Perception and Performance, 18, 347-361.
  37. Mellers, B. A., Ordonez, L. D., & Birnbaum, M. H. (1992). A change-of-process theory for contextual effects and preference reversals in risky decision making. Organizational Behavior and Human Decision Processes, 52, 319-330.
  38. Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Re- view, 84 : 231-259.
  39. Nisbett, R. E., Zukier, H., & Lemley, R. (1981). The dilution effect: Nondiagnostic information. Cognitive Psychology, 13, 248-277.
  40. Norman, K. (1976). A solution for weights and scales in functional measurement. Psychological Review, 84, 231-259.
  41. Parducci, A. (1965). Category judgment: A range-frequency model. Psychological Review, 72, 407-418.
  42. Parducci, A. (1968). The relativism of absolute judgment. Scien- tific American, 219, 84-90.
  43. Parducci, A. (1974). Contextual effects: A range-frequency anal- ysis.
  44. In E. C. Carterette & M. P. Friedman (Eds.), Handbook of perception (Vol. 2, pp. 127-141). San Diego, CA: Academic Press.
  45. Parducci, A., & Perrett, L. (1971). Category rating scales: Effects of relative spacing and frequency of stimulus values. Journal of Experimental Psychology, 89, 427-452.
  46. Poulton, E. C. (1968). The new psychophysics: Six models for magnitude estimation. Psychological Bulletin, 69, 1-19.
  47. Ronis, D. L., & Lipinski, E. R. (1985). Value and uncertainty as weighting functions in impression formation. Journal of Person- ality and Social Psychology, 21, 47-60.
  48. Slovic, P., Griffin, D., & Tversky, A. (1990). Compatibility effects in judgment and choice. In R. Hogarth (Ed.), Insights in decision making (pp. 5-27). Chicago: University of Chicago Press.
  49. Slovic, P., & Lichtenstein, S. (1983). Preference reversals: A broader perspective. American Economic Review, 73, 596-605.
  50. Stewart, T. R., & Ely, D. W. (1984). Range sensitivity: A neces- sary condition and a test for the validity of weights. Unpublished manuscript.
  51. Surber, C. (1981). Effects of information reliability in predicting task performance using ability and effort. Journal of Personality and Social Psychology, 40, 977-989.
  52. Teghtsoonian, R. (1971). On the exponents in Steven's law and the constant in Ekman's law. Psychological Review, 78, 71-80.
  53. Troutman, C. M., & Shanteau, J. (1977). Inferences based on nondiagnostic information. Journal of Personality and Social Psychology, 43, 1163-1174.
  54. Tversky, A., Sattath, S., & Slovic, P. (1988). Contingent Weighting in judgment and choice. Psychological Review, 95, 371-384.
  55. von Nitzsch, R., & Weber, M. (in press). The effect of attribute ranges on weights in multiattribute utility measurements. Man- agement Science.
  56. von Winterfeldt, D., & Edwards, W. (1986). Decision analysis and behavioral research. Cambridge, England: Cambridge Univer- sity Press.
  57. Weber, M. (1992). Behavioral influences on weight judgments in multiattribute decision making. Unpublished manuscript. Received December 14, 1992 Revision received November 1, 1993 Accepted February 16, 1994 • 1995 APA Convention Call for Programs The Call for Programs for the 1995 APA annual convention appears in the September issue of the APA Monitor. The 1995 convention will be held in New York, New York, from August 11 through August 15. The deadline for submission of program and presentation proposals is December 2,1994. Additional copies of the Call are available from the APA Convention Office, effective in September. As a reminder, agreement to participate in the APA convention is now presumed to convey permission for the presentation to be audiotaped if selected for taping. Any speaker or participant who does not wish his or her presentation to be audiotaped must notify the person submitting the program either at the time the invitation is extended or before the December 2 deadline for proposal submission.

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