Abstract
Already at a very young age, one learns to weigh options, develop scenarios in one’s mind and create an image of reality that is pleasant. In order to do that, one asked questions such as “why?”
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Notes
- 1.
Bryman notes, most regretfully that “in only 18 % of articles were the two sets of findings genuinely integrated” (Bryman in Bergman (Eds.) 2008, p. 98).
- 2.
Miles and Huberman (2003, p. 78) stipulate that an expert in this regard should (1) be familiar with the field under investigation; (2) display an interest in conceptualization; (3) show interest in multidisciplinary research efforts; and (4) be able to talk to people.
- 3.
Example: Maxwell et al. (2009).
- 4.
Boutin is cited as follows (2008, p. 46): Sometimes, traditional methods (close-ended questions, standardized tests, etc.) fail to provide us with access to essential data: attitudes, perceptions, representations, etc. (author’s translation).
- 5.
“15 % of replication studies in the social science of marketing fully confirmed the prior findings and only 25 % partially confirmed them” Sobh and Perry (2006, p. 1197).
- 6.
Patton (1990, p. 12) writes: “The purpose of applied research and evaluation is to inform action, enhance decision making, and apply knowledge to solve human and societal problems.”
- 7.
Multitrait-multimethod.
- 8.
Hurmerinta-Peltomäki and Nummela (2006, p. 439).
- 9.
Bryman in Bergman (Eds.) (2008, p. 98).
- 10.
Buchanan and Bryman (2007, p. 486).
- 11.
See, among others, Brinberg and McGrath (1985), Brewer and Hunter (1989), Babbie (1989), Brannen (1992), Neuman (1994), Maxwell and Loomis (2003), Sobh and Perry (2006).
- 12.
For more information on reasons for conducting multiple methodological research, see Brannen (1992), Munro and Mingers (2002), Hanson et al. (2005), or Hurmerinta-Peltomäki and Nummela (2006).
- 13.
See Yin 1997, 1999; Rispal 2002.
- 14.
“A major source of uncertainty is that any study employing a single type of research method—and most studies still use only one method—leaves untested rival hypotheses (or alternative interpretations of data) that call the validity of the study’s findings into question” (Brewer and Hunter 1989, p. 14).
- 15.
Miller and Salkind (2002).
- 16.
Which Morse (2003) in Tashakkori and Teddlie (2003, p. 190) would call integrity.
- 17.
See Tashakkori and Teddlie (2003).
- 18.
Loftus and Palmer (1974).
- 19.
Van Bruggen et al. (2002, p. 470) present the following arguments: (1) one source could produce errors or systematic biases; (2) no one can be an expert on everything, including on all the elements of a model; (3) a larger number of experts helps to reduce errors due to chance.
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Mesly, O. (2015). More on Data Percolation. In: Creating Models in Psychological Research. SpringerBriefs in Psychology. Springer, Cham. https://doi.org/10.1007/978-3-319-15753-5_5
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DOI: https://doi.org/10.1007/978-3-319-15753-5_5
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