Assessing and analysing individual differences in change over time is of central scientific
importance to developmental neuroscience. However, the literature is based largely on …

The lack of sufficient big data-based approaches impedes the development of human
resource management (HRM) research and practices. Although scholars have realized the …

Inferring reciprocal effects or causality between variables is a central aim of behavioral and
psychological research. To address reciprocal effects, a variety of longitudinal models that …

Structural equation modeling is an ideal data analytical tool for testing complex relationships
among many analytical variables. It can simultaneously test multiple mediating and …

The potential for big data to provide value for psychology is significant. However, the pursuit
of big data remains an uncertain and risky undertaking for the average psychological …

The introduction to this special issue on psychological research involving big data
summarizes the highlights of 10 articles that address a number of important and inspiring …

Methodological innovations have allowed researchers to consider increasingly
sophisticated statistical models that are better in line with the complexities of real-world …

追踪研究当中, 交叉滞后模型可以探究多变量之间往复式影响, 潜增长模型可以探究个体增长
趋势. 对两类模型进行整合, 例如同时关注往复式影响与个体增长趋势, 同时可以定义测量误差 …

It is well established that brain structures and cognitive functions change across the life
span. A long-standing hypothesis called “age differentiation” additionally posits that the …

The current study explored the associations between non–cognitive science-related
variables, ie, science interest, utility, self-efficacy, science identity, and science achievement …