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Updated: Sep 9, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
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Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

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国際オンライン教育評価システムからのログデータの分析:アクションシーケンス間の反応時間に対する多州生存モデリングアプローチ

Jina Park1,2, Ick Hoon Jin1,2, Minjeong Jeon3

  • 1Department of Applied Statistics, https://ror.org/01wjejq96Yonsei University, Seoul, South Korea.

Psychometrika
|September 1, 2025
PubMed
まとめ

この研究では,オンラインの評価ログデータを分析するために,複数の状態の生存モデル (MSM) を導入します. このモデルは,受験者に対する要因の影響を明らかにする.

キーワード:
主要な行動ログデータマルチステート生存モデル問題解決テスト反応時間

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Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
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Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
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Survival Curves01:18

Survival Curves

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Censoring Survival Data

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