Theory analysis in data evaluation is an essential component of qualitative research. It's a method to discover and define the most important concepts that arise from data. Some researchers combine deductive and inductive codes and rely on the inductive method of creating theories directly from data. This article will expose some best practices for theory analysis in qualitative studies with a particular emphasis on the Grounded Theory method.

GT is a method of research that is based on the hypothesis of new theories being developed through the collection and analysis of real-world data. It is a popular choice to research complex subjects, especially those that have limited or no research to guide it. Instead of establishing an idea and then gathering data to prove it or disprove, the grounded-theory method starts with a general question about a phenomenon, and then conducts interviews to discover the specifics of how that phenomenon operates. The interview transcripts are then coded to create categories that represent facets of the data. This process is repeated until the researcher is theoretically saturation, after which there are no more interviews added to the theory. MAXQDA offers several coding methods that are used extensively in GT including "in-vivo" coding that utilizes the actual words or phrases from the transcripts as codes. This allows researchers to quickly www.notesjungle.com/theory-analysis-in-data-evaluation and easily identify important excerpts in the data to be analyzed. Additionally, the capability to color code a particular section or a set of codes in MAXQDA can be beneficial for GT because it increases researchers' ability to perceive the data and allows them to find important information that would otherwise be overlooked.