The Analysis and Interpretation of Multivariate Data for Social Scientists

By David J. Bartholomew, Irini Moustaki, J. Galbraith, F. Steele. 2002

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Citations in the corpus

Working Memory and Children’s Mathematical Skills: Implications for mathematical development and mathematics curricula (2006, methodology): “For the present analysis Ward’s method was selected as it typically yields the clearest picture of clustering and can be used on data that are not metric to produce “meaningful” clusters (Bartholomew et al., 2002).”
The Resource Generator: social capital quantification with concrete items (2005, background): “M. Van Der Gaag, T.A.B. Snijders / Social Networks 27 (2005) 1–29 7”
The measurement and influence of child sexual abuse supportive beliefs (2007, methodology): “Using the exploratory sample, a principal components analysis (PCA) was conducted in order to ascertain the numbers of factors to extract using Factor Analysis (Bartholomew, Steele, Moustaki, & Galbraith, 2002 ).”
ltm: An R Package for Latent Variable Modeling and Item Response Theory Analyses (2006, methodology): “An example with ordinal data The data we consider here come from the Environment section of the 1990 British Social Attitudes Survey (Brook, Taylor, and Prior 1991; Bartholomew et al. 2002).”
The analysis of social networks (2008, methodology): “Algorithms including multidimensional scaling (Bartholomew et al. 2002) and spring embedders (Fruchterman and Reingold 1991) now are often used to position units/actors in Cartesian space by optimizing some function of the network data and the spatial coordinates for units.”
A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form (2018, methodology): “Parallel analysis using polychoric correlations ( Galbraith et al., 2002 ), another technique to recently emerge, was used to analyse two eShopping datasets, which we labelled eShopping1 and eShopping2 and that were collected as part of the ﬁrst author ’s dissertation, to examine the number of…”
Learning the Structure of Linear Latent Variable Models (2006, methodology): “The traditional framework for discovering latent variables is factor analysis and its variants (see, e.g., Bartholomew et al., 2002).”