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Is Smoking As Deadly As You Think? A Research Methods Perspective

Author

Listed:
  • Richard Tansey

    () (College of Business Administration, Texas A&M International University, Laredo, Texas 78041)

  • Michael White

    () (Department of Management and Information Systems, College of Business and Industry, Mississippi State University, Mississippi State, Mississippi 39762-9581)

  • James Collins

    () (School of Management, University of Alaska, Fairbanks, Alaska 99775)

Abstract

During the recent tobacco wars between the US cigarette industry and antismoking groups, estimates of the public health dangers attributable to domestic cigarette consumption played a pivotal role in persuading government officials and consumers to support regulatory restrictions. Antismoking persons generally argue that cigarettes are high in risk and low in benefits and may support this stereotype by pointing to the US surgeon general's (1989) estimate of attributable risk that over 400,000 American adults die annually from smoking-related diseases. However, most people are unaware of the statistical calculations behind these estimates. The Doll-Peto population-attributable-risk ( PAR ) results dominated Business Week 's (1982) coverage of the tobacco wars.

Suggested Citation

  • Richard Tansey & Michael White & James Collins, 2004. "Is Smoking As Deadly As You Think? A Research Methods Perspective," Interfaces, INFORMS, vol. 34(4), pages 280-286, August.
  • Handle: RePEc:inm:orinte:v:34:y:2004:i:4:p:280-286
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    File URL: http://dx.doi.org/10.1287/inte.1040.0080
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    References listed on IDEAS

    as
    1. Viscusi, W Kip, 1990. "Do Smokers Underestimate Risks?," Journal of Political Economy, University of Chicago Press, vol. 98(6), pages 1253-1269, December.
    2. repec:aph:ajpbhl:1975:65:9:939-953_5 is not listed on IDEAS
    3. repec:aph:ajpbhl:1972:62:2:152-158_2 is not listed on IDEAS
    4. Sterling, T. & Weinkam, J., 1990. "The confounding of occupation and smoking and its consequences," Social Science & Medicine, Elsevier, vol. 30(4), pages 457-467, January.
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    Keywords

    health care; epidemiology; statistics; estimation;

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