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Research Writing and Analysis

This page contains information to support researchers with various research tools..

Trustworthiness of Qualitative Data

As noted in the dissertation template for qualitative studies, the section directly following the Chapter 4 introduction is to be labeled Trustworthiness of the Data, and in this section, qualitative researchers are required to articulate evidence of four primary criteria to ensure trustworthiness of the final study data set:

Credibility (e.g., triangulation, member checks)

Credibility of qualitative data can be assured through multiple perspectives throughout data collection to ensure data are appropriate. This may be done through data, investigator, or theoretical triangulation; participant validation or member checks; or the rigorous techniques used to gather the data.

Transferability (e.g., the extent to which the findings are generalizable to other situations)

Generalizability is not expected in qualitative research, so transferability of qualitative data assures the study findings are applicable to similar settings or individuals. Transferability can be demonstrated by clear assumptions and contextual inferences of the research setting and participants.

Dependability (e.g., an in-depth description of the methodology and design to allow the study to be repeated)

Dependability of the qualitative data is demonstrated through assurances that the findings were established despite any changes within the research setting or participants during data collection. Again, rigorous data collection techniques and procedures can assure dependability of the final data set.

Confirmability (e.g., the steps to ensure that the data and findings are not due to participant and/or researcher bias)

Confirmability of qualitative data is assured when data are checked and rechecked throughout data collection and analysis to ensure results would likely be repeatable by others. This can be documented by a clear coding schema that identifies the codes and patterns identified in analyses. Finally, a data audit prior to analysis can also ensure dependability.

For more information on these criteria, visit the Sage Research Methods database in the NU Library: https://resources.nu.edu/sagerm