| 英文摘要 |
This article provide a summary for statistical and computational methods that have been designed and developed via addressing issues or solving problems directly relevant to psychological research. The topics include: (a) Theory of psychological measurement (classical and item response theories), (b) Causal inference (continuous and discrete data analyses), (c) Hierarchical data analysis (general and Bayesian approaches), (d) Exact test (randomization and population models), (e) Bayesian network, (f) Social network, and (g) Multidimensional scaling. With a few examples, this article illustrates how the quantitative methods when properly used promote wonderful discoveries in psychology. The examples also support the uniqueness and importance of quantitative methods for psychological research. Finally. the article suggests a few important issues (i.e., incomplete-data collection and analyses, and an integration of statistics and informatics) for studies on quantitative methods in the future. |
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