Thematic Coding and Analysis
Thematic coding and analysis have become the most usual methods of qualitative analysis. In carrying out a thematic analysis, the researchers categorize the number of items and relevant data that will adequately replicate their recorded data. The researchers should familiarize with the data when the analysis comes to be insightful and expedite. This calls for the researchers collecting and transcribing the data themselves.
Proceeding data familiarization, the researchers usually code the data. They apply fleeting verbal explanations to small masses of data. This process varies depending on the setting which includes the researcher’s prospects concerning the direction the analysis proceeds in. The analyst makes coding after approximately two to three ranks of text. However, there are no rules regulating these operations; thus, one analysis can be coded more densely than others.
It is important for the researcher to modify and alter the coding properly. After coding basic information, it is important to categorize important sets. This is a complicated method and, therefore, the researcher should define every theme sufficiently for others to understand. Examples should be illustrated to effectively demonstrate the results of the analysis. In addition, the researcher should integrate numerical indications to show the incidence and prevalence of every issue regarding their data.
The majority of qualitative researchers agree that data trustworthiness, whether composed from unswerving focus groups, interviews or observations, is always evidenced by dependability, transferability, conformability and credibility (Lincoln & Guba 1985). The data trustworthiness can be ensured by various procedures described by Merriam (2009) as triangulation, or having multiple foundations of data as a proof, arranging for data providers to appraise conclusions, continuous data composition to the point of saturation, where more collection adds little to the regularity, consultation with professionals, carrying out audit trail, offering rich explanation of the study’s perspective and plausible alternatives, which means the basis for ruling out alternative details and accounting for negative cases. The rigor and trustworthiness of a qualitative study and its data analysis is also enhanced by a procedure known as pattern matching (Trochim 2000). This is a strategy for affiliating data to analysis, design, theoretical propositions and qualitative data.