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Lala_Diss_07.04.2017.pdf (462.62 KB)

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Decomposing Variance Components for Risk Perceptions Using Generalizability Theory

Wang, Yi
http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1498785199689687

Abstract Details

2017, Doctor of Philosophy (Ph.D.), Bowling Green State University, Psychology/Industrial-Organizational.
Generalizability of a risk perception measure is essential to make inferences and predictions based on the measured risk perception ratings. The present study used generalizability (G) theory to examine the generalizability of risk perception ratings across people. Archival data with risk perception ratings of samples from three different countries, United States, Japan, and China (total n = 617), were used for generalizability (G) and decision (D) studies based on G theory. For the combined sample, the G study results showed large variance across domain and small variance across people. But there was also considerable variance due to random errors, which may confound with the interaction effect between persons and activities in specific domains. Compared to the combined sample, the magnitudes of variance components were slightly different when examining the subsamples of males and females, and those from the United States, Japan, and China. D study results showed that sufficient generalizability could be achieved from risk perception ratings by a small number of raters, but this number vary across different population groups, and across different risk domains.
Scott Highhouse, Dr. (Advisor)
Margaret Brooks, Dr. (Committee Member)
Richard Anderson, Dr. (Committee Member)
Lubomir Popov, Dr. (Committee Member)
74 p.
Psychology
risk; perception; generalizability theory; psychometrics

Recommended Citations

Citations

  • Wang, Y. (2017). Decomposing Variance Components for Risk Perceptions Using Generalizability Theory [Doctoral dissertation, Bowling Green State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1498785199689687

    APA Style (7th edition)

  • Wang, Yi. Decomposing Variance Components for Risk Perceptions Using Generalizability Theory. 2017. Bowling Green State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1498785199689687.

    MLA Style (8th edition)

  • Wang, Yi. "Decomposing Variance Components for Risk Perceptions Using Generalizability Theory." Doctoral dissertation, Bowling Green State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1498785199689687

    Chicago Manual of Style (17th edition)

bgsu1498785199689687
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© 2017, all rights reserved.
This open access ETD is published by Bowling Green State University and OhioLINK.