國立虎尾科技大學 |

Analysis of Functional Magnetic Resonance Imaging Data : = A Comparison of Extended Unified Structural Equation Modeling (euSEM) and Generalized Structured Components Analysis (GSCA).

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Analysis of Functional Magnetic Resonance Imaging Data :/
其他題名:	A Comparison of Extended Unified Structural Equation Modeling (euSEM) and Generalized Structured Components Analysis (GSCA).
作者:	Lipton, Abraham K.
面頁冊數:	1 online resource (178 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-01, Section: B.
Contained By:	Dissertations Abstracts International84-01B.
標題:	Quantitative psychology. -
電子資源:	click for full text (PQDT)
ISBN:	9798834057505

Analysis of Functional Magnetic Resonance Imaging Data : = A Comparison of Extended Unified Structural Equation Modeling (euSEM) and Generalized Structured Components Analysis (GSCA).
Lipton, Abraham K.

Analysis of Functional Magnetic Resonance Imaging Data :A Comparison of Extended Unified Structural Equation Modeling (euSEM) and Generalized Structured Components Analysis (GSCA). - 1 online resource (178 pages)

Source: Dissertations Abstracts International, Volume: 84-01, Section: B.

Thesis (Ph.D.)--Fordham University, 2022.

Includes bibliographical references

Structural Equation Modeling (SEM) is a broad family of models which can be utilized to assess the relationship between latent variables. In the context of fMRI analysis, extended unified SEM (euSEM) and Generalized structured components analysis (GSCA) represent two different SEM approaches. This dissertation examined how these models perform under non-normality, low correlations between indicators, and model misspecification via simulations. The four criteria used to assess the performance were bias, Type I error, power, and convergence percentage. The results from the simulations were applied to an empirical dataset. In summary, GSCA was found to be more powerful but also more biased than euSEM. This was true for all levels of normality, correlation, and model specification.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798834057505Subjects--Topical Terms:

1182802
Quantitative psychology.
Subjects--Index Terms:

GSCAIndex Terms--Genre/Form:

554714
Electronic books.

Analysis of Functional Magnetic Resonance Imaging Data : = A Comparison of Extended Unified Structural Equation Modeling (euSEM) and Generalized Structured Components Analysis (GSCA).
LDR:02229ntm a22003737 4500 001 1142424
005 20240422070828.5
006 m o d
007 cr mn ---uuuuu
008 250605s2022 xx obm 000 0 eng d
020 $a 9798834057505
035 $a (MiAaPQ)AAI29170023
035 $a AAI29170023
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Lipton, Abraham K. $3 1466740
245 1 0 $a Analysis of Functional Magnetic Resonance Imaging Data : $b A Comparison of Extended Unified Structural Equation Modeling (euSEM) and Generalized Structured Components Analysis (GSCA).
264 0 $c 2022
300 $a 1 online resource (178 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 84-01, Section: B.
500 $a Advisor: Kim, Se-Kang;Cham, Hei.
502 $a Thesis (Ph.D.)--Fordham University, 2022.
504 $a Includes bibliographical references
520 $a Structural Equation Modeling (SEM) is a broad family of models which can be utilized to assess the relationship between latent variables. In the context of fMRI analysis, extended unified SEM (euSEM) and Generalized structured components analysis (GSCA) represent two different SEM approaches. This dissertation examined how these models perform under non-normality, low correlations between indicators, and model misspecification via simulations. The four criteria used to assess the performance were bias, Type I error, power, and convergence percentage. The results from the simulations were applied to an empirical dataset. In summary, GSCA was found to be more powerful but also more biased than euSEM. This was true for all levels of normality, correlation, and model specification.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Quantitative psychology. $3 1182802
650 4 $a Medical imaging. $3 1180167
653 $a GSCA
653 $a Structural equation modeling
653 $a Statistical power
653 $a Magnetic resonance imaging
655 7 $a Electronic books. $2 local $3 554714
690 $a 0632
690 $a 0574
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Fordham University. $b Psychology. $3 1186654
773 0 $t Dissertations Abstracts International $g 84-01B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29170023 $z click for full text (PQDT)