Using Monte Carlo Simulation to Forecast the Scientific Utility of Psychological App Studies: A Tutorial [0.03%]
利用蒙特卡洛模拟预测心理应用研究的科学效用：教学教程
Sebastian Kueppers,Richard Rau,Florian Scharf
Sebastian Kueppers
Mobile applications offer a wide range of opportunities for psychological data collection, such as increased ecological validity and greater acceptance by participants compared to traditional laboratory studies. However, app-based psycholog...
Integrating Intra- and Interindividual Phenomena in Psychological Theories [0.03%]
心理理论中整合个体内部和个体间现象
Denny Borsboom,Jonas Haslbeck
Denny Borsboom
Psychological science is divided into two distinct methodological traditions. One tradition seeks to understand how people function at the individual level, while the other seeks to understand how people differ from each other. Methodologie...
Benedikt Langenberg,Jonathan L Helm,Axel Mayer
Benedikt Langenberg
Latent repeated measures ANOVA (L-RM-ANOVA) has recently been proposed as an alternative to traditional repeated measures ANOVA. L-RM-ANOVA builds upon structural equation modeling and enables researchers to investigate interindividual diff...
Parametric g-formula for Testing Time-Varying Causal Effects: What It Is, Why It Matters, and How to Implement It in Lavaan [0.03%]
用于测试时变因果效应的参数g公式：它是什么，为什么重要以及如何在Lavaan中实现它
Wen Wei Loh,Dongning Ren,Stephen G West
Wen Wei Loh
Psychologists leverage longitudinal designs to examine the causal effects of a focal predictor (i.e., treatment or exposure) over time. But causal inference of naturally observed time-varying treatments is complicated by treatment-dependent...
Gemma Hammerton,Jon Heron,Katie Lewis et al.
Gemma Hammerton et al.
Latent classes are a useful tool in developmental research, however there are challenges associated with embedding them within a counterfactual mediation model. We develop and test a new method "updated pseudo class draws (uPCD)" to examine...
Multilevel Latent Differential Structural Equation Model with Short Time Series and Time-Varying Covariates: A Comparison of Frequentist and Bayesian Estimators [0.03%]
短时间序列和时变协变量的多层次潜在差异结构方程模型：频率学派估计与贝叶斯估计的比较
Young Won Cho,Sy-Miin Chow,Christina M Marini et al.
Young Won Cho et al.
Continuous-time modeling using differential equations is a promising technique to model change processes with longitudinal data. Among ways to fit this model, the Latent Differential Structural Equation Modeling (LDSEM) approach defines lat...
Finite Mixtures of Latent Trait Analyzers With Concomitant Variables for Bipartite Networks: An Analysis of COVID-19 Data [0.03%]
具有伴随变量的有限潜在特征分析混合模型在二分网络中的应用：对COVID-19数据进行分析
Dalila Failli,Maria Francesca Marino,Francesca Martella
Dalila Failli
Networks consist of interconnected units, known as nodes, and allow to formally describe interactions within a system. Specifically, bipartite networks depict relationships between two distinct sets of nodes, designated as sending and recei...
The Effects of Questionnaire Length on the Relative Impact of Response Styles in Ambulatory Assessment [0.03%]
问卷长度对日间评估中反应风格相对影响的效应
Kilian Hasselhorn,Charlotte Ottenstein,Thorsten Meiser et al.
Kilian Hasselhorn et al.
Ambulatory assessment (AA) is becoming an increasingly popular research method in the fields of psychology and life science. Nevertheless, knowledge about the effects that design choices, such as questionnaire length (i.e., number of items ...
Linear Mixed-Effects Models for Dependent Data: Power and Accuracy in Parameter Estimation [0.03%]
依赖数据的线性混合效应模型：参数估计中的功效与精确度
Yue Liu,Kit-Tai Hau,Hongyun Liu
Yue Liu
Linear mixed-effects models have been increasingly used to analyze dependent data in psychological research. Despite their many advantages over ANOVA, critical issues in their analyses remain. Due to increasing random effects and model comp...
Testing Conditional Independence in Psychometric Networks: An Analysis of Three Bayesian Methods [0.03%]
心理测量网络中条件独立性的检验：三种贝叶斯方法的分析
Nikola Sekulovski,Sara Keetelaar,Karoline Huth et al.
Nikola Sekulovski et al.
Network psychometrics uses graphical models to assess the network structure of psychological variables. An important task in their analysis is determining which variables are unrelated in the network, i.e., are independent given the rest of...