‘Perhaps the most fundamental barriers to good comparative research are measurement and the problems of comparability of measures.’ (Peters, 1998, p. 80) A quick glance at the contents of this book reveals that this is a bold statement. Given the sheer number of challenges we face designing our research projects, it might even be an overstatement. But whether or not we share Peters’ view, measurement as the link between theory and empirical reality is the backbone of empirical research and therefore at the core of research design, irrespective of whether research is quantitative or qualitative (based on large-n or small-n), or, for that matter, whether it is comparative or not. The central role of measurement in research design goes some way to explain the skepticism of one distinguished commentator on the subject who is ‘doubtful, that any amount of study … can teach you how to measure social phenomena, though it can conceivably be helpful in understanding xactly what is achieved by a proposed method of measurement or measuring instrument’ (Duncan, 1984, p. 154). This is what this chapter sets out to do.
- Latent Variable
- Content Validity
- Validity Test
- Observe Variable
- Aggregation Rule
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© 2007 Bernhard Miller
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Miller, B. (2007). Making Measures Capture Concepts: Tools for Securing Correspondence between Theoretical Ideas and Observations. In: Gschwend, T., Schimmelfennig, F. (eds) Research Design in Political Science. Palgrave Macmillan, London. https://doi.org/10.1057/9780230598881_5
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-28564-8
Online ISBN: 978-0-230-59888-1