?
О некоторых методических аспектах исследования индивидуальности человека
Human individuality, presented on different levels (from biological to social ones), is of a high interest in Russian psychology, and the method of correlation design is widely used among researches, because it allows revealing relationships between multi-level properties of individuality. The present article examines several methodical aspects of the correlation analysis implementation, discussing problems and possible solutions. In particular, it considers the issue of nonlinear dependencies (parabolic, hyperbolic etc.), which are impossible to reveal by common correlation methods, but which can be uncovered by using nonlinear correlations, such as correlation index, correlation ratio, maximal information coefficient, distance correlation, maximal correlation, “partial moments” method. Furthermore, it considers the necessity of visualizing variables correlation (scatterplots) that enables to reveal hidden data structures, for example, subgroups. Special attention is paid to correlations corrections for restriction of range and related difficulties that are well-known, but scarcely researched in Russian psychology. In process of investigating plentiful pairwise correlations between individuality properties on different levels it is important to consider anissue of multiple comparisons, which, however, is rarely taken into the account by researches, leading to false results in many occasions. Moreover, the article examines robust statistical methods, particularly permutation tests and bootstrap. These methods combine robustness and high power. Finally, the study observes such issues as the completeness of results presentation and current debates about significance level, effect size and confidence intervals, reproducibility of psychological researches, and meta-analysis approach. Significance level has often been criticized; interval estimates and effect size were supposed to replace it. However, the problem of Null Hypothesis Significance Testing (NHST) has not been completely solved yet. A possible solution is presentation of complete data on research results including precise significance level, confidence intervals, effect size and etc. These estimations can be then applied in meta-analysis, which allows moving on to a new level of scientific generalizations.