東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Modelling Conditional Dependence Bet...

Bezirhan, Ummugul,

Linked to FindBook

Google Book

Amazon

博客來

Modelling Conditional Dependence Between Response Time and Accuracy in Cognitive Diagnostic Models /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modelling Conditional Dependence Between Response Time and Accuracy in Cognitive Diagnostic Models // Ummugul Bezirhan.
Author:	Bezirhan, Ummugul,
Description:	1 electronic resource (115 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 82-08, Section: B.
Contained By:	Dissertations Abstracts International82-08B.
Subject:	Educational tests & measurements. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28314205
ISBN:	9798569966110

Modelling Conditional Dependence Between Response Time and Accuracy in Cognitive Diagnostic Models /
Bezirhan, Ummugul,

Modelling Conditional Dependence Between Response Time and Accuracy in Cognitive Diagnostic Models /Ummugul Bezirhan. - 1 electronic resource (115 pages)

Source: Dissertations Abstracts International, Volume: 82-08, Section: B.

With the novel data collection tools and diverse item types, computer-based assessments allow to easily obtain more information about an examinee's response process such as response time (RT) data. This information has been utilized to increase the measurement precision about the latent ability in the response accuracy models. van der Linden's (2007) hierarchical speed-accuracy model has been widely used as a joint modelling framework to harness the information from RT and the response accuracy, simultaneously. The strict assumption of conditional independence between response and RT given latent ability and speed is commonly imposed in the joint modelling framework. Recently multiple studies (e.g., Bolsinova & Maris, 2016; Bolsinova, De Boeck, & Tijmstra, 2017a; Meng, Tao, & Chang, 2015) have found violations of the conditional independence assumption and proposed models to accommodate this violation by modelling conditional dependence of responses and RTs within a framework of Item Response Theory (IRT). Despite the widespread usage of Cognitive Diagnostic Models as formative assessment tools, the conditional joint modelling of responses and RTs has not yet been explored in this framework. Therefore, this research proposes a conditional joint response and RT model in CDM with an extended reparametrized higher-order deterministic input, noisy 'and' gate (DINA) model for the response accuracy. The conditional dependence is modelled by incorporating item-specific effects of residual RT (Bolsinova et al., 2017a) on the slope and intercept of the accuracy model. The effects of ignoring the conditional dependence on parameter recovery is explored with a simulation study, and empirical data analysis is conducted to demonstrate the application of the proposed model. Overall, modelling the conditional dependence, when applicable, has increased the correct attribute classification rates and resulted in more accurate item response parameter estimates.

English

ISBN: 9798569966110Subjects--Topical Terms:

3168483
Educational tests & measurements.
Subjects--Index Terms:

Hierarchical speed-accuracy model

Modelling Conditional Dependence Between Response Time and Accuracy in Cognitive Diagnostic Models /
LDR:03374nmm a22004213i 4500 001 2431045
005 20250603110640.5
006 m o d
007 cr|nu||||||||
008 261011s2021 miu||||||m |||||||eng d
020 $a 9798569966110
035 $a (MiAaPQD)AAI28314205
035 $a AAI28314205
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Bezirhan, Ummugul, $e author. $3 3819670
245 1 0 $a Modelling Conditional Dependence Between Response Time and Accuracy in Cognitive Diagnostic Models / $c Ummugul Bezirhan.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 1 electronic resource (115 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: 82-08, Section: B.
500 $a Advisors: Lee, Young-Sun.
502 $b Ph.D. $c Columbia University $d 2021.
520 $a With the novel data collection tools and diverse item types, computer-based assessments allow to easily obtain more information about an examinee's response process such as response time (RT) data. This information has been utilized to increase the measurement precision about the latent ability in the response accuracy models. van der Linden's (2007) hierarchical speed-accuracy model has been widely used as a joint modelling framework to harness the information from RT and the response accuracy, simultaneously. The strict assumption of conditional independence between response and RT given latent ability and speed is commonly imposed in the joint modelling framework. Recently multiple studies (e.g., Bolsinova & Maris, 2016; Bolsinova, De Boeck, & Tijmstra, 2017a; Meng, Tao, & Chang, 2015) have found violations of the conditional independence assumption and proposed models to accommodate this violation by modelling conditional dependence of responses and RTs within a framework of Item Response Theory (IRT). Despite the widespread usage of Cognitive Diagnostic Models as formative assessment tools, the conditional joint modelling of responses and RTs has not yet been explored in this framework. Therefore, this research proposes a conditional joint response and RT model in CDM with an extended reparametrized higher-order deterministic input, noisy 'and' gate (DINA) model for the response accuracy. The conditional dependence is modelled by incorporating item-specific effects of residual RT (Bolsinova et al., 2017a) on the slope and intercept of the accuracy model. The effects of ignoring the conditional dependence on parameter recovery is explored with a simulation study, and empirical data analysis is conducted to demonstrate the application of the proposed model. Overall, modelling the conditional dependence, when applicable, has increased the correct attribute classification rates and resulted in more accurate item response parameter estimates.
546 $a English
590 $a School code: 0054
650 4 $a Educational tests & measurements. $3 3168483
650 4 $a Statistics. $3 517247
650 4 $a Education. $3 516579
653 $a Hierarchical speed-accuracy model
653 $a Latent variable models
653 $a Response Time data
653 $a Cognitive diagnostic models
690 $a 0288
690 $a 0463
690 $a 0515
710 2 $a Columbia University. $b TC: Measurement and Evaluation. $e degree granting institution. $3 3819671
720 1 $a Lee, Young-Sun $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 82-08B.
790 $a 0054
791 $a Ph.D.
792 $a 2021
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28314205