As stated above, relational analysis builds on conceptual analysis by examining the relationships among concepts in a text. Studies have been conducted with as few as one and as many as 500 concept categories. Obviously, too many categories may obscure your results and too few can lead to unreliable and potentially invalid conclusions. Therefore, it is important to allow the context and necessities of your research to guide your coding procedures. There are many techniques of relational analysis available and this flexibility makes for it's popularity.
Researchers can devise their own procedures according to the nature of their project.
Once a procedure is rigorously tested, it can be applied and compared across populations over time. The process of relational analysis has achieved a high degree of computer automation but still is, like most forms of research, time consuming. Perhaps the strongest claim that can be made is that it maintains a high degree of statistical rigor without losing the richness of detail apparent in even more qualitative methods. The issues of reliability and validity are concurrent with those addressed in other research methods. The overarching problem of concept analysis research is the challengeable nature of conclusions reached by its inferential procedures.