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  1. Kevin Patrick Tobia, Gretchen B. Chapman & Stephen Stich (2013). Cleanliness is Next to Morality, Even for Philosophers. Journal of Consciousness Studies 20 (11-12).
    A number of studies have shown that seemingly morally irrelevant factors influence the moral judgments of ordinary people. Some argue that philosophers are experts and are significantly less susceptible to such effects. We tested whether an unconscious cleanliness prime – the smell of Lysol – affects the judgments of both non-philosophers and professional philosophers. Our results suggest that the direction of cleanliness effects depends both on the respondent and whether the question is framed in the second or third person. They (...)
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  2. Marta T. Suárez, Gretchen B. Chapman & Natalie A. Obrecht (2011). Laypeople Do Use Sample Variance: The Effect of Embedding Data in a Variance-Implying Story. Thinking and Reasoning 16 (1):26-44.
    When using sample data to decide whether two populations differ, laypeople attend to the difference between group means, but largely overlook within-group variability (Obrecht, Chapman, & Gelman, 2007). We show, first, that laypeople know about and use story-implied variability when making pairwise comparisons. Then we demonstrate that participants' sensitivity to variance in a dataset is boosted when presented in a context that implies consistent variance information. Statistical data were couched in stories about electrical conductivity measurements obtained from element samples (low-variability (...)
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  3. Natalie A. Obrecht, Gretchen B. Chapman & Marta T. Suárez (2010). Laypeople Do Use Sample Variance: The Effect of Embedding Data in a Variance-Implying Story. Thinking and Reasoning 16 (1):26 – 44.
    When using sample data to decide whether two populations differ, laypeople attend to the difference between group means, but largely overlook within-group variability (Obrecht, Chapman, & Gelman, 2007). We show, first, that laypeople know about and use story-implied variability when making pairwise comparisons. Then we demonstrate that participants' sensitivity to variance in a dataset is boosted when presented in a context that implies consistent variance information. Statistical data were couched in stories about electrical conductivity measurements obtained from element samples (low-variability (...)
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  4. Gretchen B. Chapman, Noel T. Brewer, Elliot J. Coups, Susan Brownlee, Howard Leventhal & Elaine A. Levanthal (2001). Value for the Future and Preventive Health Behavior. Journal of Experimental Psychology: Applied 7 (3):235.
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  5. Gretchen B. Chapman & Arthur S. Elstein (2000). Cognitive Processes and Biases in Medical Decision Making. In Gretchen B. Chapman & Frank A. Sonnenberg (eds.), Decision Making in Health Care: Theory, Psychology, and Applications. Cambridge University Press. 183--210.
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  6. Gretchen B. Chapman & Frank A. Sonnenberg (eds.) (2000). Decision Making in Health Care: Theory, Psychology, and Applications. Cambridge University Press.
    Decision making is a crucial element in the field of medicine. The physician has to determine what is wrong with the patient and recommend treatment, while the patient has to decide whether or not to seek medical care, and go along with the treatment recommended by the physician. Health policy makers and health insurers have to decide what to promote, what to discourage, and what to pay for. Together, these decisions determine the quality of health care that is provided. Decision (...)
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  7. Gretchen B. Chapman, Richard Nelson & Daniel B. Hier (1999). Familiarity and Time Preferences: Decision Making About Treatments for Migraine Headaches and Crohn's Disease. Journal of Experimental Psychology: Applied 5 (1):17.
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  8. Brian H. Bornstein & Gretchen B. Chapman (1995). Learning Lessons From Sunk Costs. Journal of Experimental Psychology: Applied 1 (4):251.
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