Book contents
- Frontmatter
- Contents
- List of Tables and Figures
- Acknowledgments
- Introduction
- PART I FRAMEWORK
- PART II POPULAR ATTITUDES TO REFORM
- PART III COMPETING EXPLANATIONS
- PART IV EXPLAINING REFORM CONSTITUENCIES
- Conclusions
- Appendices
- A Items, Constructs, and Indices
- B Sampling Method
- C Imputation of Data
- Notes
- Index
- Cambridge Studies in Comparative Politics
A - Items, Constructs, and Indices
Published online by Cambridge University Press: 15 December 2009
- Frontmatter
- Contents
- List of Tables and Figures
- Acknowledgments
- Introduction
- PART I FRAMEWORK
- PART II POPULAR ATTITUDES TO REFORM
- PART III COMPETING EXPLANATIONS
- PART IV EXPLAINING REFORM CONSTITUENCIES
- Conclusions
- Appendices
- A Items, Constructs, and Indices
- B Sampling Method
- C Imputation of Data
- Notes
- Index
- Cambridge Studies in Comparative Politics
Summary
ITEMS, CONSTRUCTS, AND INDICES
This appendix lists all indicators from the regression and path analyses presented in Chapters 6 through 12.
Three types of indicator are employed. Single items are used where a concept is measured with one survey question. We report the verbatim wording of questions along with the frequency distributions of responses. The accuracy (validity and reliability) of single-item indicators is based on the correspondence of the item's wording with the underlying concept (face validity), its association with other theoretically expected correlates (construct validity) or, eventually, test-retest reliability through longitudinal analysis. We also use several two-item constructs, the composition of which is reported here. In this case, validity and reliability are established by the methods already mentioned, but also by examining interitem correlation (Pearson's r) and internal consistency (Cronbach's Alpha). Wherever possible, we use multiitem indices, again reporting how these are constructed. These indices allow us to establish validity through factor analysis (which measures how each observed item relates to a hypothesized latent construct) and reliability analysis (Cronbach's Alpha).
There are many different combinations of factor analysis. To err on the side of caution, we almost always apply the most stringent methods, that is, maximum likelihood extraction and direct oblimin rotation, guaranteeing that if a factor solution can be found, it will also be found via all other methods. Test statistics from factor and reliability analyses are cited in order to establish the accuracy of all multiitem indices.
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- Public Opinion, Democracy, and Market Reform in Africa , pp. 355 - 391Publisher: Cambridge University PressPrint publication year: 2004