Considering the 'With Whom': Differences Between Event- and Signal-Contingent ESM Data of Person-Specific Social Interactions [0.03%]
考虑交往对象：事件触发式和信号触发式生态 moment 社会互动测量的差异性分析
Marie Stadel,Marijtje A J van Duijn,Aidan G C Wright et al.
Marie Stadel et al.
Experience sampling studies often aim to capture social interactions. A central methodological question in such studies is whether to use event- or signal-contingent sampling. The little existing research on this issue has not taken into ac...
Lourens Waldorp,Jonas Haslbeck
Lourens Waldorp
Calculating confidence intervals and p-values of edges in networks is useful to decide their presence or absence and it is a natural way to quantify uncertainty. Since lasso estimation is often used to obtain edges in a network, and the und...
A Confidence Interval for the Difference Between Standardized Regression Coefficients [0.03%]
标准化回归系数之差的置信区间
Samantha F Anderson
Samantha F Anderson
Researchers are often interested in comparing predictors, a practice commonly done via informal comparisons of standardized regression slopes. However, formal interval-based approaches offer advantages over informal comparison. Specifically...
On the Selection of Item Scores or Composite Scores for Clinical Prediction [0.03%]
项目分数或复合分数在临床预测中的选择
Kenneth McClure,Brooke A Ammerman,Ross Jacobucci
Kenneth McClure
Recent shifts to prioritize prediction, rather than explanation, in psychological science have increased applications of predictive modeling methods. However, composite predictors, such as sum scores, are still commonly used in practice. Th...
Samuel D Aragones,Emilio Ferrer
Samuel D Aragones
An important goal when analyzing multivariate time series is the identification of heterogeneity, both within and across individuals over time. This heterogeneity can represent different ways in which psychological processes manifest, eithe...
Correcting Regression Coefficients for Collider Bias in Psychological Research [0.03%]
心理研究中纠正回归系数的共因偏差
Sophia J Lamp,David P MacKinnon
Sophia J Lamp
Collider bias is a statistical phenomenon that occurs when a researcher adjusts for a common outcome variable that is shared between a predictor and its criterion. This biased adjustment can happen in one of two ways: (1) treating the colli...
Detecting Cohort Effects in Accelerated Longitudinal Designs Using Multilevel Models [0.03%]
使用多层模型在加速纵列设计中识别队列效应
Simran K Johal,Emilio Ferrer
Simran K Johal
Accelerated longitudinal designs allow researchers to efficiently collect longitudinal data covering a time span much longer than the study duration. One important assumption of these designs is that each cohort (a group defined by their ag...
Propensity Score Weighting with Missing Data on Covariates and Clustered Data Structure [0.03%]
具有协变量缺失数据和聚类数据结构的倾向性评分加权方法
Xiao Liu
Xiao Liu
Propensity score (PS) analyses are increasingly popular in behavioral sciences. Two issues often add complexities to PS analyses, including missing data in observed covariates and clustered data structure. In previous research, methods for ...
Information Matrix Test for Item Response Models Using Stochastic Approximation [0.03%]
信息矩阵检验项目反应模型使用随机逼近的方法
Youngjin Han,Yang Liu,Ji Seung Yang
Youngjin Han
Kayla M Garner
Kayla M Garner