Abstract
In this chapter, modeling and providing general principles of conducting research are discussed. This is part of the data percolation methodology that will be explained throughout this book.
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- 1.
See Jarvis et al. 2003.
- 2.
Olivier and Payette (2010, p. 18) about modeling: group of concepts linked together by some sense of coherence and definition, giving a simplification of reality.
- 3.
Brousselle et al. (2009, p. 60) explain that modeling is meant to make intelligible a complex reality not to make complex a simple reality!
- 4.
The term structural is not related to structural equation modeling (SEM).
- 5.
The reason why we need at least two subconstructs to form a single construct stems from the fact that we want define construct by what it is and what it is not (black and white). Therefore, a construct is necessarily formed by at least two subconstructs.
- 6.
Bollen and Lennox (1991, p. 308): “Omitting an indicator is omitting a part of the construct.”
- 7.
Structural variables are akin to formative variables in psychological statistics (Diamantopoulos et al. 2008).
- 8.
See Diamantopoulos and Winklhofer 2001; Diamantopoulos and Siguaw 2006.
- 9.
Collier and Bienstock (2009, p. 284) mention that formative variables in statistics are theoretically uncorrelated or sometimes negatively correlated.
- 10.
“Continuous” in the sense that it is not binary. In a true sense, the scale is not continuous but ‘elongated’ although the measurement could be continuous. For all intents and purposes, we use the term ‘continuous’.
- 11.
Creswell (1994, p. 85) mentions: “Position the dependent variable on the right in the diagram and the independent variables on the left.”
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Mesly, O. (2015). Bubbles and Arrows. In: Creating Models in Psychological Research. SpringerBriefs in Psychology. Springer, Cham. https://doi.org/10.1007/978-3-319-15753-5_2
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DOI: https://doi.org/10.1007/978-3-319-15753-5_2
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