AF Measure Analysis Issues IV: Redundancy, correlation, complementarity, subjective scales validation (uses of principal components & factor analyses)
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Watch the video (includes video guide)
Roche, J.M. (2008). Monitoring Inequality among Social Groups: A Methodology Combining Fuzzy Set Theory and Principal Component Analysis. Journal of Human Development. Vol. 9 (3)
Rutstein, S. and K. Johnson, 2004. The DHS Wealth Index, DHS Comparative Reports No. 6, Calverton, MD: ORC Macro.
Klasen, S. (2000). Measuring Poverty and Deprivation in South Africa. Review of Income and Wealth. Vol. 46, pp. 33-58.
Brown, T. A. (2006) Confirmatory factor analysis for applied research, New York, NY ; London, New York, NY ; London : Guilford Press. (Chapter 2: The common Factor Model and Exploratory Factor Analysis)
Gagne, M., Forest, M.J., Gilbert, M.-H., Aube, C., Morin,E. and Malorni, A. (2010). The Motivation at Work Scale: Validation Evidence in Two Languages. Educational and Psychological Measurement. Vol. 70 (4), pp. 628-646.
Normative Issues in Multidimensional Poverty Measurement
Guide to video
00:00 Introduction
02:42 Outline of the lecture
03:51 Definition of factor analysis, relate to latent variable analysis
08:28 Example of Rustein and Jonston (2004) Wealth Index, principal component analysis
11:37 Other options besides factor analysis (data reduction)
16:58 Example of Lelli (2008), factor analysis vs. fuzzy set theory
Part 1: Exploratory and Confirmatory Factor Analysis
22:08 Definition of exploratory (unrestricted) factor analysis (EFA); calculation steps
27:54 Example of principle component analysis (Klasen, 2000), here weight are based on the correlations between indicators – a statistical solution (see also Normative Issues in Multidimensional Poverty Measurement for choice of weights)
33:30 Confirmatory factor analysis – restricted analysis. Look in Brown’s book both for exploratory and confirmatory reference Brown (2006)
39:50 Literature overview on the goodness of fit
Part 2: Empirical Implementation of Exploratory Factor Analysis
41:16 The different step of exploratory factor analysis (Brown (2006))
43:03 Step 1: the example of Roche 2008
44:46 Step 2: extraction method
46:30 Step 3: determination of appropriate number of factors; sources – Kaiser criterion, Analysis of Scree plot, parallel analysis, normative judgement
52:07 Step 4: method of rotation to obtain your simple structural model, orthogonal and oblique rotation
61:40 Example of Roche (2008), rotation results – construct 3 indices based on factor analysis, discuss weight (link to lecture on normative issues)
70:04 Step 5: interpretation an evaluation of the quality of the solution
70:19 Example of Roche (2008), results of different models
75:28 Example of Galla and Roche (2011), the implicit weight arising from different clusters of variables
76:24 Tetrachoric correlations
77:29 Example Galla and Roche (2011), results
Part 3: Subjective Scale Validation
81:11 Subjective scale validation
81:50 Psychometric evaluation
81:32 Example of Gagne et al (2009), autonomy and work
84:33 The process of subjective scale variation
84:57 Techniques for the different stages of scale validation
85:22 Crombach Alpha
86:05 Example of Steger et al (2006), subjective scale validation, the meaning of life
87:30 Example, subjective scale validation, psychological needs
88:57 Exploratory factor analysis results
91:20 Complementary factor analysis results
92:10 Strength and weaknesses of factor analysis
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For supplementary reading on this topic view
Reading List on Factor Analysis
Reading List on Scale Validation
