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--- en:general:indices [02.04.2015 17:32] – oezbf2012
+++ en:general:indices [30.04.2021 09:42] (current) – [Frequently Asked Questions] sophia.schauer
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 The calculation of a scale index is only sensible if all items reflect the same construct. In practice you can test this by computing the correlation between the items by means of Cronbach's alpha.
 As a rule of thumb Cronbach's alpha should be above .7. However, Cronbach's alpha is highly influenced by the amount of items. Therefore a scale with only 4 or 5 items can be plausible with an alpha value of .6.
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 Yes and no. In principle the size of the correlation is independent from the number of items. However, in a neatly constructed scale the quality of the measurement is increased by the number of items. Therefore the scale index contains fewer measurement errors and as a result higher correlations may be observed.
-To the contrary a correlation based on more items can actually be overrated if both constructs underlie the same measurement error. The higher correlation with more items is a spurious correlation in this case – e.g. because some people prefer to answer on the right end of the scale (acquiescence).
+On the contrary a correlation based on more items can actually be overrated if both constructs underlie the same measurement error. The higher correlation with more items is a spurious correlation in this case – e.g. because some people prefer to answer on the right end of the scale (acquiescence).
 **What is the measurement level of scale indices?**
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 **Are scales with reversed-polarity items preferable?**
-This question cannot be answered in general.
+There is no general answer to this question.
 The use of reversed-polarity items will usually result in the effect that the correlation between items (Cronbach's alpha) is slightly lower. Basically that is not desirable – but might as well be an indicator that the respondents have made their answer thoughtfully. In addition, a general tendency to approval/rejection is extenuated by the use of reversed-polarity items. This results in a superior measurement of the construct.
 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.