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Psychophysical Inference from Centroid Estimation
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Psychophysical Inference from Centroid Estimation. |
| 개인저자 | Rashid, Jordan Ali. |
| 단체저자명 | University of California, Irvine. Cognitive Sciences (Ph.D./M.S.). |
| 발행사항 | [S.l.]: University of California, Irvine., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 129 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-04B. Dissertation Abstract International |
| ISBN | 9781687975409 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, Irvine, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
Advisor: Chubb, Charles. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | Performance statistics in centroid tasks are not the same as those used in classic decision tasks. In psychophysical experiments using decision tasks, signal detection theory and drift-diffusion models provide the frameworks for statistical inference from error rates and reaction times. However, neither of these frameworks are appropriate for psychophysical inference with centroid task data. In this dissertation, we explore a modeling framework for double-pass experiments with centroid tasks, and show its potential to (1) detect performance differences, and infer experimental effects without additional process model assumptions, (2) falsify properties of a latent process using nested model assumptions, (3) investigate neurocomputational models of the process, and (4) investigate properties of spatial attention at a deeper level than is possible using decision-based paradigms. |
| 일반주제명 | Cognitive psychology. Statistics. Behavioral psychology. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
