Mixed-Effects XGBoost with Group-Aware Permutation Importance and Cross-Validation for Multilevel Cross-Classified Continuous Outcomes [0.03%]
Sun-Joo Cho,Sophia Mueller
Sun-Joo Cho
This article proposes a mixed-effects machine-learning framework for modeling complex, nonlinear relations between predictors and continuous outcomes in multilevel cross-classified data. The proposed method, termed LMM-XGBoost, embeds extre...
Detecting Test Speededness Using Responses and/or Response Times: Change Point Analysis Approaches Based on Schwarz Information Criterion [0.03%]
Jing Lu,Chun Wang,Jiwei Zhang et al.
Jing Lu et al.
Change point analysis (CPA) detects structural shifts in a response sequence by partitioning it into segments with different statistical properties. This paper proposes three CPA approaches based on the Schwarz information criterion (SIC; h...
Jiguang Li,Robert Gibbons,Veronika Ročková
Jiguang Li
A Hierarchical Gaussian Process Approach to Understanding Mental Health Trajectories via Item Response Theory Models [0.03%]
基于项目反应理论的层次高斯过程理解心理健康轨迹的方法
Zoe Gibbs McBride,Xiaojing Wang
Zoe Gibbs McBride
Longitudinal mental health assessments in mobile health (mHealth) settings are useful for monitoring subjects' mental health statuses but are often difficult to analyze because they generally appear on an ordinal scale and at unequal time i...
From Digital Data to Psychological Insights: Making Sense of Mobile-Sensing Data through Integrative Preprocessing Pipelines [0.03%]
从数字数据到心理洞察：通过集成预处理流水线解析移动传感数据
Ramona Schoedel,Larissa Sust,Philipp Sterner et al.
Ramona Schoedel et al.
Psychological research has long centered around questionnaire assessments, but now digital devices, especially smartphones, enable the collection of real-world behavioral data through mobile sensing. While this data collection method offers...
Enhancing Two-Stage Estimation in Differential Equation Models: A Bias-Correction Method via Stochastic Approximation [0.03%]
基于随机逼近的微分方程模型两阶段估计偏差矫正方法
Xiaohui Luo,Hongyun Liu,Yueqin Hu et al.
Xiaohui Luo et al.
Jean-Paul Fox
Jean-Paul Fox
Does X at Time 1 Cause Y at Time 2? Longitudinal Causal Learning with Hidden Confounders [0.03%]
隐匿混淆因素下的纵向因果学习：时间1的X是否导致时间2的Y？
Dexin Shi,Wolfgang Wiedermann,Amanda J Fairchild et al.
Dexin Shi et al.
Analyzing Complex Educational Data: A Data Analytic Framework for Integrating Structured and Unstructured Eye-Tracking Data [0.03%]
复杂教育数据的分析：集成结构化和非结构化眼动数据的数据分析框架
Luyang Fang,Shiyu Wang,Yinghan Chen et al.
Luyang Fang et al.
The growing use of computer-based assessments has produced complex process data that capture learners' cognitive and behavioral processes in real time. Among these, eye-tracking data provide rich temporal information on how individuals atte...
Stefano Noventa,Andrea Spoto,Jürgen Heller et al.
Stefano Noventa et al.