Sample Size Requirements for Applying Diagnostic Classification Models.
Sample Size Requirements for Applying Diagnostic Classification Models.
复制标题
DOI:
10.3389/fpsyg.2020.621251
复制
发表时间:
2020
影响因子:
3.8
通讯作者:
Cohen AS
中科院分区:
文献类型:
--
作者:
Sen S;Cohen AS
Results of a comprehensive simulation study are reported investigating the effects of sample size, test length, number of attributes and base rate of mastery on item parameter recovery and classification accuracy of four DCMs (i.e., C-RUM, DINA, DINO, and LCDMREDUCED). Effects were evaluated using bias and RMSE computed between true (i.e., generating) parameters and estimated parameters. Effects of simulated factors on attribute assignment were also evaluated using the percentage of classification accuracy. More precise estimates of item parameters were obtained with larger sample size and longer test length. Recovery of item parameters decreased as the number of attributes increased from three to five but base rate of mastery had a varying effect on the item recovery. Item parameter and classification accuracy were higher for DINA and DINO models.
登录
查看更多内容
DOI:
10.1080/10705511.2017.1402334
发表时间:
2018
期刊:
Structural equation modeling : a multidisciplinary journal
影响因子:
--
作者:
Hallquist MN;Wiley JF
通讯作者:
Wiley JF
影响因子:
1.3
作者:
HAERTEL, EH
通讯作者:
HAERTEL, EH
影响因子:
3
作者:
De la Torre, J;Douglas, JA
通讯作者:
Douglas, JA
影响因子:
1.7
作者:
Hu, Jinxiang;Miller, M. David;Chen, Yi-Hsin
通讯作者:
Chen, Yi-Hsin
影响因子:
3
作者:
BOZDOGAN, H
通讯作者:
BOZDOGAN, H