https://scholars.lib.ntu.edu.tw/handle/123456789/630285
標題: | Comparison of Two Approaches to Detecting Switched Class Labels in LCA Simulations: Class Assignment vs. Class Similarity | 作者: | Chen, Yi Kai Yang, Tong Rong LI-JEN WENG |
關鍵字: | Class assignment algorithm | class similarity algorithm | latent class analysis | parameter estimation | simulation | switched class labels | 公開日期: | 1-一月-2023 | 出版社: | ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD | 來源出版物: | Structural Equation Modeling | 摘要: | The detection of switched class labels is required in latent class analysis (LCA) simulations involving parameter estimation. The present study proposed a class similarity (CS) algorithm to detect switched class labels based on the similarity of conditional probabilities between true and estimated classes, in contrast to Tueller et al.’s class assignment (CA) algorithm considering the number of participants in each true class assigned to every estimated class. The performances of CS and CA were compared by examining the average class assignment accuracy and the bias of parameter estimates in a numerical experiment. CS and CA were shown to perform similarly that either method can be used to detect switched class labels in future LCA simulations. The performance of the two algorithms warrants further investigation under a wider simulation condition. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/630285 | ISSN: | 10705511 | DOI: | 10.1080/10705511.2023.2183502 |
顯示於: | 心理學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。