摘要：The article presents a new method of normalization – normalization with respect to pattern (or pattern normalization in short). It has properties expected for this type of transformation: preserves skewness, kurtosis and the Pearson correlation coefficients. Although pattern normalization uses only observations from the current unit of time, it can be used in dynamic research. An additional advantage of new normalization is the ability to reflect different analysis environments. The effects of pattern normalization are illustrated by an empirical example. Indicators monitoring the implementation of the Europe 2020 Strategy are used. Normalizations are carried out for two reference groups: the entire EU and countries that joined the EU in 2004. The results for two years are compared. The example of Poland shows that the “dynamic image” of the country is affected by the use of pattern normalization itself as well as by the choice of the environment. In this context pattern normalization is similar to dynamic standardization, and different than dynamic scaling.
