Theory Analysis in Data Evaluation

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Theory analysis is the process of analyzing the ideas that emerge from your data. This is an iterative, fluid process because you don’t be sure of the amount of data you need to collect in advance. Researchers who use grounded theory (GT) continuously analyze and collect new data until they reach theoretical saturated, or the point at which new data do not add to their advancing theory.

The first step in GT is to identify themes that are repeated by a thorough examination of the data. The next step is to code these emergent themes and separating them into categories through relationship identification. This process is known as open coding. It is the foundation of GT analysis. Researchers then make use of a process of constant comparison and memoing to create substantive codes or make connections between concepts. This helps to create an integrated theory by putting fragmented concepts back together into hypotheses that can be tested. Concepts are then integrated into these hypotheses through a process of axial coding.

Once the researcher has identified or has tentatively identified a central or primary variable, they then selectively sample new data in order to keep the variable in mind or to perform the process of theoretical sampling. This method restricts the scope of research and focuses only on the relevant aspects to the question.

A theory is useful not just in the area of study but also as an instrument to understand the meaning of your data and to compare and contrast various aspects. This is an essential aspect of GT analysis and should be included along with your conceptual categories and coding techniques in your methodology section.