In practice, when items are not easily created and arrayed to provide a highly reliable scale, the Q factor analysis is not necessary, since the original factor analysis should also select those items that have a common consensus. So, for instance, in a scale of items for political attitudes, the items may ask about attitudes toward big government; law and order; economic issues; labor issues; or libertarian issues. Which of these items most strongly bear on the political attitudes of the groups polled may be difficult to determine a priori. However, since factor analysis is a symmetric computation on the matrix of items and people, the original factor analysis of items, (when these are Likert scales) selects not just those items that are in a similar domain, but more generally, those items that have a similar consensus. The added advantage of this factor analytic technique is that items are automatically arranged along a factor so that the highest Likert ratings are also the highest CBA standard scores. Once selected, that factor determines the CBA (component) scores.