Credibility: reliability and validity in qualitative research

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Credibility reliability and validity in
qualitative research

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Credibility criteria for evaluation (page 222 of
Silvermann, table 8.1)

1. Are the methods of research appropriate to the
   nature of the questions being asked?
2. Is the connection to an existing body of
   knowledge or thoery clear?
3. Are there clear accounts of the criteria used for
   the selection of cases for study and of the data
   collection and analysis?
4. Does the sensitivty of the methods match the
   needs of the research questions?
5. Was the data collection and record keeping
   systematic?
6. Is reference made to accepted procedure for
   analysis?
7. How systemtic is the analysis?
8. Is there adequate discussions of how themes,
   concepts and categories were derived from the
   data?
9. Is there adequae discussion of the evidence for
   and against the researchers arguments?
10. Is a clear distinction made between the data and
    its interpretation?

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Reliability 1

• Dependability and Reliability
• The traditional quantitative view of reliability
  is based on the assumption of replicability or
  repeatability. 
• The idea of dependability, on the other hand,
  emphasizes the need for the researcher to account
  for the ever-changing context within which
  research occurs. 
• The research is responsible for describing the
  changes that occur in the setting and how these
  changes affected the way the research approached
  the study.

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Reliability 2

• Importance of making explicit aspects as
• Role of researcher
• Informant selection
• Description of Social Context
• Data collection strategies
• Data analysis strategies
• Analytical premises
• Imp of documenting

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Validity 1

• Quantitative research
• internal validity refers to the extent to which
  the findings accurately describe reality
• external validity refers to the ability to
  generalize findings across different settings
• qualitative research
• Internal validity data triangulation
• External validity generalization

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Validity 2

• Triangulation
• Compare different kinds of data
• Compare different methods
• Respondent validation

• Silvermann
• Constant comparative method
• Deviant-case analysis
• Analytic induction
• Comprehensive data treatment
• Using appropriate tabulations

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Generalizability (walsham)

• Walsham, G. (2002) Interpretive Case Studies in
  IS research Nature and Method, in Myers and
  Avison Qualitative Reaserch in Information
  Systems.
• G explanations of particular phenomena derived
  from empirical interpretative research in
  specific settings which may be vaulabe in the
  future in other organizations and contexts.
• Development of concepts
• Generation of theory
• Drawing of specific implications in particular
  domains
• Contribution of reach insight

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• Resources and references to Qualitative Research
  in Information Systems
• http//www.qual.auckland.ac.nz/