The concepts of validity and reliability are relatively foreign to the field of qualitative research-the concepts are just not a good fit. Instead of focusing on reliability and validity, qualitative researchers substitute data trustworthiness. Trustworthiness consists of the following components: (a) Credibility; (b) transferability; (c); dependability; and (d) confirmability.
Credibility contributes to a belief in the trustworthiness of data through the following attributes: (a) prolonged engagement; (b) persistent observations; (c) triangulation; (d) referential adequacy; (e) peer debriefing; and (f) member checks. Triangulation and member checks are primary and commonly used methods to address credibility.
Triangulation is accomplished by asking the same research questions of different study participants and by collecting data from different sources and by using different methods to answer those research questions. Member checks occur when the researcher asks participants to review both the data collected by the interviewer and the researchers' interpretation of that interview data. Participants are generally appreciative of the member check process, and knowing that they will have a chance to verify their statements tends to cause study participants to willingly fill in any gaps from earlier interviews. Trust is an important aspect of the member check process.
Transferability is the generalization of the study findings to other situations and contexts. Transferability is not considered a viable naturalistic research objective. The contexts in which qualitative data collection occurs defines the data and contributes to the interpretation of the data. For these reasons, generalization in qualitative research is limited.
Purposive sampling can be used to address the issue of transferability since specific information is maximized in relation to the context in which the data collection occurs. That is, specific and varied information is emphasized in purposive sampling, rather than generalized and aggregate information-which would be the case, generally, in quantitative research. Purposive sampling requires the consideration of the characteristics of the individual members of a sample in as much as those characteristics are very directly related to the research questions.
Reliability is dependent upon validity, therefore, many qualitative researchers believe that if credibility has been demonstrated, it is not necessary to also and separately demonstrate dependability. However, if a researcher permits parsing of the terms, then credibility seems more related to validity and dependability seems more related to reliability.
Sometimes data validity is assessed through the use of a data audit. A data audit can be conducted if the data set is both rich-thick so that an auditor can determine if the research situation applies to their own circumstances. Without sufficient details and contextual information, this is not possible. Regardless, it is important to remember that the aim is not to generalize beyond the sample.
A qualitative researcher must doggedly record the criteria on which category decisions are to be taken (Dey, 1993, p. 100). The ability of a qualitative researcher to use the data analysis framework flexibly, to remain open to alterations, to avoid overlaps, and to consider previously unavailable or unobservable categories, is largely dependent on the researcher's familiarity and understanding of the data. This level of data analysis is achieved by wallowing in the data (Glasser & Strauss, 1967).
Qualitative research can be conducted to replicate earlier work, and when that is the goal, it is important for the data categories to be made internally consistent. For this to happen, the researcher must devise rules that describe category properties and that can, ultimately, be used to justify the inclusion of each data bit that remains assigned to the category as well as to provide a basis for later tests of replicability (Lincoln & Guba, 1985, p. 347).
The process of refining the data within and across categories must be systematically carried out, such that the data is first organized into groups according to similar attributes that are readily apparent. Following that step, the data is put into piles and sub-piles, such that the differentiation is based on finer and finer discriminations.
Through the process of writing memos, a qualitative researcher records notes about the emergence of patterns, or the changes and considerations that are associated with the category refining process. Categorical definitions can be expected to change over the course of the study since that is fundamental to the constant comparative process-categories become less general and more specific as data is grouped and regrouped over the course of the research. In defining categories, therefore, we have to be both attentive and tentative - attentive to the data, and tentative in our conceptualizations of them (Dey, 1993, p. 102).
Dye, J.G, Schatz, I. M., Rosenberg, B. A., and Coleman, S. T. (2000, January). Constant comparison method: A kaleidoscope of data. The Qualitative Report, 4(1/2).
Glaser, B., and Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. Chicago, IL: Aldine.
Lincoln, Y. S., and Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage.