On Exact Statistical Properties of Multidimensional Indices Based on Principal Components, Factor Analysis, MIMIC and Structural Equation Models

By J. Krishnakumar, A. L. Nagar. 2008

173 citations recorded by the source corpus.

Subfields: Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/12a471218f08e41a40402619e6fc8c333f477845

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In Sociology and Political Science

Citations in the corpus

Setting weights in multidimensional indices of well-being (2008, background): “The second approach, sometimes known as latent variable models is an explanatory approach that assumes that some observed variables (dimensions) are dependent on a certain number of unobserved latent variables (Krishnakumar & Nadar 2008).”
On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness (2018, methodology): “However, according to Saisana and Tarantola (2002), the use of these approaches is not feasible in certain cases, due to either negative 11 For a review of these, see Krishnakumar and Nagar (2008), and for an illustrative example and analysis of the steps, see Greyling and Tregenna (2016).”
Multidimensional poverty and inequality (2014, unknown): “…into indices of total or domain-specific deprivation (Kuklys, 2005; Pérez-Mayo, 2005, 2007; Di Tommaso, 2007; Krishnakumar, 2008; Krishnakumar and Ballon (2008); Krishnakumar and Nagar (2008); Navarro and Ayala, 2008; Wagle, 2005, 2008a, 2008b; Tomlinson et al., 2008; Ayala et al., 2011).”
Weights in Multidimensional Indices of Wellbeing: An Overview (2013, unknown): “An early example of sensitivity of results to the choice of weights (and other parameters) can be found in Maasoumi and Nickelsburg (1988) – also in Maasoumi and Jeong (1985) and Maasoumi and Zandvakili (1986) though applied to multiple periods instead of multiple dimensions of wellbeing.”
Monitoring Inequality among Social Groups: A Methodology Combining Fuzzy Set Theory and Principal Component Analysis1 (2008, unknown): “It seems, nevertheless, that under certain circumstances both techniques can lead to similar results (cf. Velicer and Jackson, 1990; Krishnakumar and Nagar, 2007).”
Characterizing Weights in the Measurement of Multidimensional Poverty: An Application of Data-Driven Approaches to Cameroonian Data (2008, methodology): “A principal components analysis (PCA) is concerned with explaining the variancecovariance structure of a set of variables through a few linear combinations of these variables (Krishnakumar and Nagar, 2007).”