semfindr: An R Package for Identifying Influential Cases in Structural Equation Modeling [0.03%]
SEM发现者：一种用于识别结构方程模型中有影响力的案例的R软件包
Shu Fai Cheung,Mark H C Lai
Shu Fai Cheung
Measuring case influence on parameter estimates and model fit measures, which is one type of sensitivity analysis, is important for assessing the robustness of findings in structural equation modeling (SEM). However, it was rarely reported ...
Treatment Effect Moderation with Small Subgroups: An Incremental Subgroup Analysis Approach [0.03%]
基于增量的治疗效果亚组分析方法研究小样本量的调节效应问题
Xiao Liu,J Mark Eddy,Charles R Martinez Jr
Xiao Liu
Subgroup analysis is an important tool for studying treatment effect moderation. However, when a subgroup has a relatively small proportion (referred to as "focal subgroup"), standard subgroup analysis could encounter practical difficulties...
Christopher M Crawford,Jonathan J Park,Sy-Miin Chow et al.
Christopher M Crawford et al.
Interest in the study and analysis of dynamic processes in the social, behavioral, and health sciences has burgeoned in recent years due to the increased availability of intensive longitudinal data. However, how best to model and account fo...
Sijia Li,Victoria Savalei
Sijia Li
Confirmatory bifactor models have been widely applied to understand multidimensional constructs in different areas of psychology research. Maximal reliability captures how well an optimal linear composite (OLC) represents the target latent ...
Joost R van Ginkel,Dylan Molenaar
Joost R van Ginkel
In moderated factor analysis, the parameters of the traditional common factor model are a function of an external continuous moderator variable. Handling missing values on the observed indicator variables of the common factors is straightfo...
Time-Varying Path-Specific Direct and Indirect Effects: A Novel Approach to Examine Dynamic Behavioral Processes with Application to Smoking Cessation [0.03%]
时变路径特异性直接和间接效应：一种用于检查动态行为过程的新型方法及其在戒烟方面的应用
Yajnaseni Chakraborti,Recai M Yucel,Megan E Piper et al.
Yajnaseni Chakraborti et al.
Behavioral processes are often complex, and vary over time, requiring intensive longitudinal data to effectively capture the dynamic elements involved. For example, examining daily socio-behavioral and treatment adherence data collected dur...
Ethan M McCormick
Ethan M McCormick
There has been a growing interest in using earlier change to predict downstream distal outcomes in development; however, prior work has mostly focused on estimating the unique effect of the different growth parameters (e.g., intercept and s...
A Latent Space Graded Response Model for Likert-Scale Psychological Assessments [0.03%]
一种likert心理评估量表的潜在空间分级响应模型
Ludovica De Carolis,Inhan Kang,Minjeong Jeon
Ludovica De Carolis
In this study, we introduce a novel modeling approach for ordinal response data, extending the one-parameter graded response model. The proposed model incorporates unobserved interactions between respondents and items, represented as distan...
A Two-Step Robust Estimation Approach for Inferring Within-Person Relations in Longitudinal Design: Tutorial and Simulations [0.03%]
纵向设计中推断个体内部关系的两步稳健估计方法：教程与模拟研究
Satoshi Usami
Satoshi Usami
Psychological researchers have shown an interest in disaggregating within-person variability from between-person differences. This paper provides a tutorial, simulation, and illustrative example of a new approach proposed by Usami (2023). T...
Lingbo Tong,Zhiyong Zhang
Lingbo Tong
Artificial neural networks (ANN) have attracted increasing attention in the field of psychology. With the availability of software programs, the wide application of ANN becomes possible. However, without a firm understanding of the basics o...