betaselectr: Selective (and Proper) Standardization in Structural Equation Models [0.03%]
基于结构方程模型的贝塔选择标准选取方法：有选择性和规范性的标准化方法
Rong Wei Sun,Florbela Chang,Wendie Yang et al.
Rong Wei Sun et al.
Standardization is used in many common methods in psychology to enhance the interpretability of results. For example, the so-called "betas" are usually reported in structural equation modeling (SEM). However, there are three situations in w...
Exploring the Use of Multiple Imputation for Handling Missing Covariates in Meta-Regression with Dependent Effect Sizes [0.03%]
探索多重插补处理元回归中相关效应量缺失协变量的方法
Jihyun Lee,S Natasha Beretvas,Brian T Keller
Jihyun Lee
Meta-analysts frequently encounter missing covariate values, which can complicate valid estimation of meta-regression models. In practice, missing data are managed often through ad hoc deletion approaches, which can reduce the validity of s...
Suryadyuti Baral,Jonathan J Park,Emilio Ferrer
Suryadyuti Baral
Joshua R Shulkin
Joshua R Shulkin
Fair and Robust Estimation of Heterogeneous Treatment Effects for Optimal Policies in Multilevel Studies [0.03%]
分层研究中公平且稳健的异质性治疗效应估计方法及其在最优政策中的应用
Youmi Suk,Chan Park,Chenguang Pan et al.
Youmi Suk et al.
Recently, there have been growing efforts in developing fair algorithms for treatment effect estimation and optimal treatment recommendations to mitigate discriminatory biases against disadvantaged groups. While most of this work has focuse...
How to Use Residual Dynamic Structural Equation Modeling to Study Individual Differences and Intraindividual Variability in Experimental Factorial Designs: A Tutorial [0.03%]
残差动态结构方程模型在实验因子设计中研究个体差异和个体内变异性：教程
Benedikt Langenberg,Jonathan L Helm,Connor J McCabe et al.
Benedikt Langenberg et al.
This article demonstrates the application of residual dynamic structural equation modeling (RDSEM) for analyzing custom contrasts in experimental factorial designs. Previous applications of RDSEM have often focused on ecological momentary a...
Fangbin Chen,Daxun Wang,Yan Cai et al.
Fangbin Chen et al.
In standardized tests, examinees are likely to engage in either one or more following test behaviors: solution behavior, rapid guessing behavior, cheating behavior, nonresponse behavior, etc. Examinees do not always response all items with ...
Beyond Linear Risk: A Machine Learning Approach to Understanding Perinatal Depression in Context [0.03%]
超越线性风险：一种上下文下的产前抑郁机器学习分析方法
Phillip Sherlock,Maxwell Mansolf,Julie Hofheimer et al.
Phillip Sherlock et al.
The goal of this study was to investigate the contextual nature of prenatal depression (PND) and postpartum depression (PPD). We report an investigation of maternal PND and PPD using nonrandomly clustered data from 8,936 mothers in 16 cohor...
Automatic Mediation Analysis Under Measurement Error Via Bayesian Machine Learning [0.03%]
一种基于贝叶斯机器学习的测量误差下的自动中介分析方法
Xinran Song,Qian Zhang,Kaizong Ye et al.
Xinran Song et al.
This paper considers the problem of causal mediation analysis (CMA) when the outcome, mediator, or both are modeled as latent variables that are measured with error from multiple indicators. Traditional structural equation modeling approach...
Single-Level Bifactor Models as Implicit Multilevel Factor Models Without a Bifactor Structure [0.03%]
单因素模型作为无双因素结构的多水平因子模型
Christian L L Strauss,Kristopher J Preacher
Christian L L Strauss
It is well-known that bifactor structures are over-represented as preferred solutions in measurement modeling. This study explores the extent to which unmodeled clustering of observations in larger social or organization units (e.g., studen...