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--- en:general:indices [02.04.2015 17:34] – [Frequently Asked Questions] oezbf2012
+++ en:general:indices [30.04.2021 09:42] (current) – [Frequently Asked Questions] sophia.schauer
@@ Line 93: / Line 93: @@
 On the other hand, people may answer reversed-polarity items in different ways. For example, someone could avoid to answer "never" because he likes to appear especially honest. This can lead to measurement artifacts. Moreover there is some evidence that reversed-polarity items can have an impact on the unidimensionality of scales.
+**Mean values or factor values for the scale index?**
+Especially when a scale battery maps several sub-dimensions/sub-constructs, this question is at hand: For the indices of the subconstructs, should we simply average the items assigned to a subconstruct or instead work with the factor scores from an exploratory factor analysis?
+The factor scores incorporate the individual items with different weights.
+Theoretically, the factor values map the vectors of the subconstructs a bit more accurately in this way. Practically, this advantage is negligible. Practically, factor values are accompanied by a significant disadvantage: The calculation of the indices is a little different in each data set that uses the scale -- just depending on exactly how the factors lie. This means that comparability between studies is lost.
+Moreover, it should be kept in mind that the concrete factor solution (and thus the weighting) is only one of many possible solutions -- and it is in large part also the result of measurement artifacts, the choice of optimization procedure, etc...
+The lack of comparability and the influence of measurement errors argue for "normal" mean values. Such an index is usually also theoretically better supported, because in the ideal case it is already a priori clarified which items belong to which subconstruct.