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pro vyhledávání: '"C Wilbur"'
Autor:
Rebecca C. Wilbur, Emily M. Lund, Angela M. Kuemmel, Sheena Balolong Publico, Lauren R. Khazem
Publikováno v:
Psychological Services. 20:306-317
Trainees with disabilities are chronically underrepresented in psychology and face many barriers throughout their training. Directors of Clinical Training and supervisors within the Veterans Administration Healthcare System (VAHCS), one of the larges
Publikováno v:
International Journal of Research in Marketing. 40:12-21
Autor:
David C. Wilbur, Robert H. Young
Publikováno v:
International Journal of Gynecological Pathology. 42:109-119
Publikováno v:
Marketing Science. 41:873-895
This paper uses data from a new technology that passively and continuously measures TV viewer presence and attention, enabling the first distinction between true ad exposures from ads that air to empty rooms.
Akademický článek
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Akademický článek
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Autor:
Jessica Jumee Kim, Kenneth C. Wilbur
Publikováno v:
Quantitative Marketing and Economics. 20:239-273
Product acquisition policies define legal markets. Policy evaluations require data but prevalence data are not always available. We introduce Legal Firearm Prevalence (LFP), a direct behavioral measure based on the population of firearm licensees in
Publikováno v:
Journal of Empirical Legal Studies. 19:60-89
Publikováno v:
Quantitative Marketing and Economics.
We introduce the idea of beneficiary framing to the promotion response literature. Two large-scale field experiments (total N = 73,010) in the context of print-at-home coupons show that framing a savings message as affecting a beneficiary (i.e., “s
Autor:
David C Wilbur, Jason R Pettus, Maxwell L Smith, Lynn D Cornell, Alexander Andryushkin, Richard Wingard, Eric Wirch
Publikováno v:
Journal of Pathology Informatics, Vol 11, Iss 1, Pp 37-37 (2020)
Background: Prescreening of biopsies has the potential to improve pathologists' workflow. Tools that identify features and display results in a visually thoughtful manner can enhance efficiency, accuracy, and reproducibility. Machine learning for det
Externí odkaz:
https://doaj.org/article/9424b4de98e744fbae21e97e1bdc2515