Abstract: When the correlation between variables is difficult to measure by correlation coefficient, the association rules can be used to examine the relationship between the variables. The possibility of application that association rules in psychological measurement is analyzed in theoretic, then using the Apriori algorithm for mining frequent item sets to analyze cross-cultural adaptation data of foreign students. Determined questionnaire topics by interview method, then determined the formal questionnaire by exploratory factor analysis. In accordance with the international students Language, translated the formal questionnaire into English, Japanese and Korean, then distributed these formal questionnaire to 11 provinces including 16 universities, eventually obtained 651 valid questionnaires. The formal questionnaire is divided into two parts: adaptation influencing factors and adaptation level, in which adaptation influencing factors including demographic factors, social and cultural influencing factors, the school environment influencing factors and personality psychological characteristics. The Cronbach consistency coefficients of each part of the formal questionnaire is greater than 0.7. Used the data mining software Weka to implement Apriori algorithm, and set the minimum support "minsup" to 0.2, while the lowest confidence level not less than 0.6, then extracted information, and used the lift rate to evaluate the rules. Compare the results between association rules, Pearson correlation and Spearman relevant, founding that using the association rules can be more simple and effective to get the rules between variables. The results show that association rules can gain the support and confidence of each level of the variables; it can deduce the rules between the multivariate; it is very effective for dealing with the correlation in non-linear multi-variable and multi-categorical variables. This is the first time for introducing association rules method to psychological measurement; it is a very useful method for analyzing the relationship between the data.

Key words: association rules, correlation coefficient, foreign students, adaptation

摘要： 探讨了当相关系数对变量之间相关程度不易进行度量或者无法度量的情况下，是否可以采用关联规则方法来考察变量之间的相互关系。从理论上分析了关联规则方法在心理测量中应用的可能性，并运用Apriori算法挖掘频繁项集，对来华留学生跨文化适应性数据进行了分析，将关联规则方法分析结果与Pearson相关、Spearman相关结果进行比较，发现当使用关联规则方法进行相互关系分析时，能够更加简易、有效地获得变量间的相关规则。研究结果表明关联规则方法可以获得变量各个水平具体的支持度和置信度，推导出多变量之间的相关规则，并且对于处理非线性的多变量以及多分类变量的相关是非常有用的方法。

关键词: 关联规则方法 相关系数 留学生 适应性