SEARCH

SEARCH BY CITATION

References

  • Allison PD. 1999. Logistic Regression Using the SAS System: Theory and Application. SAS Institute, Inc.: Cary, NC; 308 pp.
  • AMS (American Meteorological Society). 2008. Enhancing weather information with probability forecasts. Bulletin of the American Meteorological Society 89: 10491053.
  • Ariely D, Norton MI. 2007. Psychology and experimental economics: A gap in abstraction. Current Directions in Psychological Science 16: 336339.
    Direct Link:
  • Ballinger GA. 2004. Using generalized estimating equations for longitudinal data analysis. Organizational Research Methods 7: 127150.
  • Blavatskyy P. 2007. Stochastic expected utility theory. Journal of Risk and Uncertainty 34: 259286.
  • Budescu DV, Broomell S, Por HH. 2009. Improving communication of uncertainty in the reports of the intergovernmental panel on climate change. Psychological Science 20: 299308.
    Direct Link:
  • Camerer CF. 1989. An experimental test of several generalized utility theories. Journal of Risk and Uncertainty 2: 61104.
  • Camerer CF, Hogarth R. 1999. The effects of financial incentives in economics experiments: A review and capital-labor-production framework. Journal of Risk and Uncertainty 19: 742.
  • Croson R. 2005. The method of experimental economics. International Negotiation 10: 131148.
  • Demeritt D, Cloke H, Pappenberger F, Thielen J, Bartholmes J, Ramos M-H. 2007. Ensemble predictions and perceptions of risk, uncertainty, and error in flood forecasting. Environmental Hazards 7: 115127.
  • Dillman DA. 2000. Mail and Internet Surveys: The Tailored Design Method, 2d edn. John Wiley & Sons, Inc.: New York, NY; 464 pp.
  • Fehr E, Fischbacher U, von Rosenbladt B, Schupp J, Wagner GG. 2003. A nation-wide laboratory: examining trust and trustworthiness by integrating behavioral experiments into representative survey. CESifo Working Paper Series No. 866.
  • Gigerenzer G, Hertwig R, van den Broek E, Fasolo B, Katsikopoulos KV. 2005. A 30% chance of rain tomorrow: How does the public understand probabilistic weather forecasts? Risk Analysis 25: 623629.
  • Handmer J, Proudly B. 2007. Communicating uncertainty via probabilities: The case of weather forecasts. Environmental Hazards 7: 7987.
  • Hertwig R, Ortmann A. 2001. Experimental practices in economics: A methodological challenge for psychologists? Behavioral and Brain Sciences 24: 383403.
  • Hey J. 2001. Does repetition improve consistency? Experimental Economics 4: 554.
  • Jackson DA. 1967. Acquiescence response styles: Problems of identification and control. In Response Set in Personality Assessment, BergIA (ed.). Aldine Publishing Company: Chicago, IL; 71114.
  • Joslyn S, Nadav-Greenberg L, Nichols RM. 2009a. Probability of precipitation: Assessment and enhancement of end-user understanding. Bulletin of the American Meteorological Society 90: 185193.
  • Joslyn S, Nadav-Greenberg L, Taing MU, Nichols RM. 2009b. The effects of wording on the understanding and use of uncertainty information in a threshold forecasting decision. Applied Cognitive Psychology 23: 5572.
  • Joslyn SL, Nichols RM. 2009. Probability or frequency? Expressing forecast uncertainty in public weather forecasts. Meteorological Applications 16: 309314.
  • Joslyn S, Pak K, Jones D, Pyles J, Hunt E. 2007. The effect of probabilistic information on threshold forecasts. Weather and Forecasting 22: 804812.
  • KagelJH, RothAE (eds). 1995. Handbook of Experimental Economics. Princeton University Press: Princeton, NJ; 721 pp.
  • Kahneman D, Tversky A. 1979. Prospect theory: An analysis of decision under risk. Econometrica 47: 263291.
  • Katz RW, Murphy AH. 1997. Forecast value: Prototype decision-making models. In Economic Value of Weather and Climate Forecasts, KatzRW, MurphyAH (eds). Cambridge University Press: Cambridge, UK; 183217.
  • Krosnick JA. 1991. Response strategies for coping with the cognitive demands of attitude measures in surveys. Applied Cognitive Psychology 5: 213236.
  • Kühberger A. 1998. The influence of framing on risky decisions: A meta-analysis. Organizational Behavior and Human Decision Processes 75: 2355.
  • Lazo JK, Morss RE, Demuth JL. 2009. 300 billion served: Sources, perceptions, uses, and values of weather forecasts. Bulletin of the American Meteorological Society 90: 785798.
  • Lazo JK, Waldman DM, Morrow BH, Thacher JA. 2010. Household evacuation decision making and the benefits of improved hurricane forecasting: Developing a framework for assessment. Weather and Forecasting 25: 207219.
  • Levin IP, Schneider SL, Gaeth GJ. 1998. All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes 76: 149188.
  • Lipkus IM, Samsa G, Rimer BK. 2001. General performance on a numeracy scale among highly educated samples. Medical Decision Making 21: 3744.
  • Loewenstein G. 1999. Experimental economics from the vantage-point of behavioural economics. Economic Journal 109: F23F34.
  • Manning MR. 2003. The difficulty of communicating uncertainty. Climatic Change 61: 916.
  • Morss RE, Demuth J, Lazo JK. 2008. Communicating uncertainty in weather forecasts: A survey of the U.S. public. Weather and Forecasting 23: 974991.
  • Morss RE, Wilhelmi OV, Downton MW, Gruntfest E. 2005. Flood risk, uncertainty, and scientific information for decision-making: Lessons from an interdisciplinary project. Bulletin of the American Meteorological Society 86: 15931601.
  • Murphy AH, Lichtenstein S, Fischoff B, Winkler RL. 1980. Misinterpretations of precipitation probability forecasts. Bulletin of the American Meteorological Society 61: 695701.
  • Mylne K. 2002. Decision-making from probability forecasts based on forecast value. Meteorological Applications 9: 307315.
  • Nadav-Greenberg L, Joslyn S, Taing MU. 2008. The effect of weather forecast uncertainty visualization on decision-making. Journal of Cognitive Engineering and Decision Making 2: 2447.
  • Naef M, Schupp J. 2009. Measuring trust: Experiments and surveys in contrast and combination. SOEP paper No. 167.
  • von Neumann J, Morgenstern O. 1944. Theory of Games and Economic Behavior. Princeton University Press: Princeton, NJ.
  • Novak DR, Bright DR, Brennan MJ. 2008. Operational forecaster uncertainty needs and future roles. Weather and Forecasting 23: 10691084.
  • NRC (National Research Council). 2003. Communicating Uncertainties in Weather and Climate Information: A Workshop Summary. National Academies Press: Washington, DC; 68 pp.
  • NRC. 2006. Completing the Forecast: Characterizing and Communicating Uncertainty for Better Decisions Using Weather and Climate Forecasts. National Academies Press: Washington, DC; 124 pp.
  • O'Connell AA. 2005. Logistic Regression Models for Ordinal Response Variables. Sage Publications: Thousand Oaks, CA; 120 pp.
  • Palmer TN. 2002. The economic value of ensemble forecasts as a tool for risk assessment: From days to decades. Quarterly Journal of the Royal Meteorological Society 128: 747774.
  • Peters E, Västfjäll D, Slovic P, Mertz CK, Mazzocco K, Dickert S. 2006. Numeracy and decision making. Psychological Science 17: 407413.
    Direct Link:
  • Richardson DS. 2000. Skill and economic value of the ECMWF ensemble prediction system. Quarterly Journal of the Royal Meteorological Society 126: 649668.
  • Roulston MS, Bolton GE, Kleit AN, Sears-Collins AL. 2006. A laboratory study of the benefits of including uncertainty information in weather forecasts. Weather and Forecasting 21: 116122.
  • Roulston MS, Kaplan TR. 2008. A laboratory-based study of understanding of uncertainty in 5-day site-specific temperature forecasts. Meteorological Applications 16: 237244.
  • Ryan RT. 2003. Digital forecasts: Communication, public understanding, and decision making. Bulletin of the American Meteorological Society 84: 10011003.
  • Santos P, Sharp DW, Rader G, Volkmer M. 2008. Employing hurricane wind probabilities to convey forecast uncertainty and potential impact through NWS field office forecast products. Proceedings of 19th Conference on Probability and Statistics, New Orleans, LA, 21–24 Jan 2008. American Meteorological Society: Boston, MA.
  • Schuman H, Presser S. 1996. Questions and Answers in Attitude Surveys: Experiments on Question Form, Wording, and Context. Sage Publications: Thousand Oaks, CA; 372 pp.
  • Sink SA. 1995. Determining the public's understanding of precipitation forecasts: Results of a survey. National Weather Digest 9: 915.
  • Smith VL, Walker J. 1993. Monetary rewards and decision cost in experimental economics. Economic Inquiry 31: 245261.
  • Starmer C, Sugden R. 1989. Probability and juxtaposition effects: An experimental investigation of the common ratio effect. Journal of Risk and Uncertainty 2: 159178.
  • Thompson JC. 1952. On the operational deficiencies in categorical weather forecasts. Bulletin of the American Meteorological Society 33: 223226.
  • Thompson JC, Brier GW. 1955. The economic utility of weather forecasts. Monthly Weather Review 83: 249254.
  • Tourangeau R, Rips LJ, Rasinski K. 2000. The Psychology of Survey Response. Cambridge University Press: Cambridge, UK; 416 pp.
  • Tversky A, Kahneman D. 1981. The framing of decisions and the psychology of choice. Science 211: 453458.
  • Tversky A, Kahneman D. 1992. Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty 5: 297323.
  • U.S. Census Bureau. 2006. 2006 American Community Survey. Available online at http://www.census.gov/acs/www/. Accessed 2007.
  • Windschitl PD, Weber EU. 1999. The interpretation of “likely” depends on the context, but “70%” is 70%—right?: The influence of associative processes on perceived certainty. Journal of Experimental Psychology: Learning, Memory, and Cognition 25: 15141533.
  • Zhu Y, Toth Z, Wobus R, Richardson D, Mylne K. 2001. On the economic value of ensemble-based weather forecasts. Bulletin of the American Meteorological Society 83: 7383.