Coding and Data Analysis Process in Qualitative Research

¶ … Coding and Data Analysis Process in Qualitative Research

"Coding is the process of combing the data for themes, ideas and categories and then marking similar passages of text with a code label so that they can easily be retrieved at a later stage for further comparison and analysis. Coding the data makes it easier to search the data, to make comparisons and to identify any patterns that require further investigation" (Taylor & Gibbs 2010). Coding is a critical aspect of qualitative research as without effective coding there is nothing but a sea of potentially interesting but not necessarily useable data. It could also be argued that during the coding process analysis is already taking place, given that qualitative research is empirical and proceeds 'from the ground up:' during the coding process, the theory or ideas about the subject matter are only just beginning to take shape. Some codes before the data is recorded may come from pre-existing categories but other codes may arise organically from the data. Bits of data may be 'coded' more than once in some instances if they fall under two categories. Also, data may be coded according to, for example, race and gender of respondents rather than the content of the response alone.

Although coding may sound 'numeric,' qualitative research is about turning non-numerical data into analyzable chunks: there is no quantifiable hypothesis before the research takes place. The lack of a hypothesis is one reason why quantitative researchers occasionally criticize qualitative approaches as unscientific. However, by having two separate individuals code the data and then reconciling them, objections about bias may be quelled. "Qualitative research is more defensible when multiple coders are used and when high inter- and intra-coder reliability are obtained. Intercoder reliability refers to consistency among different coders. Intracoder reliability refers to consistency within a single code" (Chapter 17: Qualitative data, 2014).

Another method of remaining objective about the data is a technique called 'constant comparison. "Every time you select a passage of text (or its equivalent in video etc.) and code it, you should compare it with all those passages you have already coded that way, perhaps in other cases. This ensures that your coding is consistent and allows you to consider the possibility either that some of the passages coded that way don't fit as well (and might therefore be better codes as something else) or that there are dimensions or phenomena in the passages that might well be coded another way as well" (Taylor & Gibbs 2010). The researcher is thus always reevaluating the data for new possibilities and refining the coding process.