Toward a Psychology of Individuals: The Ergodicity Information Index and a Bottom-up Approach for Finding Generalizations [0.03%]
个体心理学之路：遍历性信息指数与自下而上寻找一般化的途径
Hudson Golino,John Nesselroade,Alexander P Christensen
Hudson Golino
In the last half of the twentieth century, psychology and neuroscience have experienced a renewed interest in intraindividual variation. To date, there are few quantitative methods to evaluate whether a population (between-person) structure...
Lijin Zhang,Wen Qu,Zhiyong Zhang
Lijin Zhang
Growth curve modeling has been widely used in many disciplines to understand the trajectories of growth. Two popular forms utilized in the real-world analyses are the linear and quadratic growth curve models. These models operate on the ass...
Missing Data in Discrete Time State-Space Modeling of Ecological Momentary Assessment Data: A Monte-Carlo Study of Imputation Methods [0.03%]
生态瞬时评估数据中离散时间状态空间模型的缺失数据问题：插补方法的蒙特卡罗研究
L R Slipetz,A Falk,T R Henry
L R Slipetz
When using ecological momentary assessment data (EMA), missing data is pervasive as participant attrition is a common issue. Thus, any EMA study must have a missing data plan. In this paper, we discuss missingness in time series analysis an...
Correcting for Differences in Measurement Unreliability in Meta-Analysis of Variances [0.03%]
元分析中方差测量不可靠性的差异校正
Katrin Jansen,Steffen Nestler
Katrin Jansen
There is a growing interest of researchers in meta-analytic methods for comparing variances as a means to answer questions on between-group differences in variability. When measurements are fallible, however, the variance of an outcome refl...
Exploring the Effects of Sampling Variability, Scale Variability, and Node Aggregation on the Consistency of Estimated Networks [0.03%]
探索采样变异性、尺度变异性及节点聚合对估计网络一致性的影响
Arianne Herrera-Bennett,Mijke Rhemtulla
Arianne Herrera-Bennett
Work surrounding the replicability and generalizability of network models has increased in recent years, prompting debate on whether network properties can be expected to be consistent across samples. To date, certain methodological practic...
Model Selection for Mixed-Effects Location-Scale Models with Confidence Interval for LOO or WAIC Difference [0.03%]
混合效应位置尺度模型的选择以及LOO或WAIC差异的置信区间
Yue Liu,Fan Fang,Hongyun Liu
Yue Liu
LOO (Leave-One-Out cross-validation) and WAIC (Widely Applicable Information Criterion) are widely used for model selection in Bayesian statistics. Most studies select the model with the smallest value based on point estimates, often withou...
A Tutorial on the Use of Artificial Intelligence Tools for Facial Emotion Recognition in R [0.03%]
使用人工智能工具在R中进行面部情绪识别的教程
Austin Wyman,Zhiyong Zhang
Austin Wyman
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion ...
Autoencoders for Amortized Joint Maximum Likelihood Estimation of Confirmatory Item Factor Models [0.03%]
确认性项目因子模型的联合极大似然估计的自编码器算法研究
Dylan Molenaar,Raoul P P P Grasman,Mariana Cúri
Dylan Molenaar
Neural networks like variational autoencoders have been proposed as a statistical tool to fit item factor models to data. Advantages are that high dimensional models can be estimated more efficiently as compared to conventional approaches. ...
TDCM: An R Package for Estimating Longitudinal Diagnostic Classification Models [0.03%]
TDCM：一个用于估计纵向诊断分类模型的R包
Matthew J Madison,Minjeong Jeon,Michael Cotterell et al.
Matthew J Madison et al.
Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or non-proficiency of specified latent attributes. Longitudinal DCMs have recently been developed as psychometric ...
Interrater Reliability for Interdependent Social Network Data: A Generalizability Theory Approach [0.03%]
广义测量理论在社会网络数据互倚性检验中的应用研究
Debby Ten Hove,Terrence D Jorgensen,L Andries van der Ark
Debby Ten Hove
We propose interrater reliability coefficients for observational interdependent social network data, which are dyadic data from a network of interacting subjects that are observed by external raters. Using the social relations model, dyadic...