Integrated Trend and Lagged Modeling of Multi-Subject, Multilevel, and Short Time Series [0.03%]
多主体、多层次和短时间序列的综合趋势与滞后建模方法研究
Xiaoyue Xiong,Yanling Li,Michael D Hunter et al.
Xiaoyue Xiong et al.
Trends represent systematic intra-individual variations that occur over slower time scales that, if unaccounted, are known to yield biases in estimation of momentary change patterns captured by time series models. The applicability of detre...
Han Du,Fang Liu,Zhiyong Zhang et al.
Han Du et al.
Bayesian statistics have gained significant traction across various fields over the past few decades. Bayesian statistics textbooks often provide both code and the analytical forms of parameters for simple models. However, they often omit t...
Monica Morell,Muwon Kwon,Youngjin Han et al.
Monica Morell et al.
A regression discontinuity (RD) design is often employed to provide causal evidence when the randomization of the treatment assignment is infeasible. When variables of interest are latent constructs measured by observed indicators, the conv...
Targeted Maximum Likelihood Estimation for Causal Inference With Observational Data-The Example of Private Tutoring [0.03%]
基于观察数据的因果推断中的靶向极大似然估计-以私教为例
Christoph Jindra,Karoline A Sachse
Christoph Jindra
State-of-the-art causal inference methods for observational data promise to relax assumptions threatening valid causal inference. Targeted maximum likelihood estimation (TMLE), for example, is a template for constructing doubly robust, semi...
Detecting Transition Points in the Slope-Intercept Relation in Linear Latent Growth Models [0.03%]
线性潜在增长模型中斜率截距关系转换点的检测
Dayeon Lee,Gregory R Hancock
Dayeon Lee
In a linear latent growth model parameterized by intercept (α) and slope (β) factors, those factors' relation is often of interest. The model typically captures this through their covariance parameter, which inherently assumes linearity i...
Multilevel Metamodels: Enhancing Inference, Interpretability, and Generalizability in Monte Carlo Simulation Studies [0.03%]
多层次元模型：在蒙特卡洛模拟研究中增强推断、可解释性和泛化能力
Joshua B Gilbert,Luke W Miratrix
Joshua B Gilbert
Metamodels, or the regression analysis of Monte Carlo simulation results, provide a powerful tool to summarize simulation findings. However, an underutilized approach is the multilevel metamodel (MLMM) that accounts for the dependent data s...
Sample Size Determination for Optimal and Sub-Optimal Designs in Simplified Parametric Test Norming [0.03%]
简化参数测试常态化的最优和亚最优设计的样本量确定方法研究
Francesco Innocenti,Alberto Cassese
Francesco Innocenti
Norms play a critical role in high-stakes individual assessments (e.g., diagnosing intellectual disabilities), where precision and stability are essential. To reduce fluctuations in norms due to sampling, normative studies must be based on ...
Bayesian Multilevel Compositional Data Analysis with the R Package multilevelcoda [0.03%]
具有R包multilevelcoda的贝叶斯多层次组成数据分析
Flora Le,Dorothea Dumuid,Tyman E Stanford et al.
Flora Le et al.
Multilevel compositional data, such as data sampled over time that are non-negative and sum to a constant value, are common in various fields. However, there is currently no software specifically built to model compositional data in a multi...
Correlated Residuals in Lagged-Effects Models: What They (Do Not) Represent in the Case of a Continuous-Time Process [0.03%]
滞后效应模型中的相关残差：在连续时间过程的情况下它们（不）代表什么
R M Kuiper,E L Hamaker
R M Kuiper
The appeal of lagged-effects models, like the first-order vector autoregressive (VAR(1)) model, is the interpretation of the lagged coefficients in terms of predictive-and possibly causal-relationships between variables over time. While the...
The Effects of Data Preprocessing Choices on Behavioral RCT Outcomes: A Multiverse Analysis [0.03%]
数据预处理选择对行为RCT结果的影响：多重分析法
Giuseppe A Veltri
Giuseppe A Veltri
Seemingly routine data-preprocessing choices can exert outsized influence on the conclusions drawn from randomized controlled trials (RCTs), particularly in behavioral science where data are noisy, skewed and replete with outliers. We demon...