For a more technical treatment of some of the topics later in the module, I recommend “Latent Variable Models and Factor Analysis: A Unified Approach” Bartholomew, Knott, and Moustaki (2011), which is available online via the UCL library
Latent Dirichlet Analysis is a method for class mixture modelling, particularly useful for analysing word count data.
Correspondent analysis is, roughly speaking, principle components analysis for count data.
Multidimensional scaling methods simplify a large number of distance measures into coordinates in a small number of dimensions, almost always 2. They provide a way to take multiple senses of distance and simplify them into something that looks like a map.
Confirmatory factor analysis and structural equation modelling are tools for modelling relationships between observed and latent variables, and are a book-length topic in their own right. In principle, structural equation modelling allow one to integrate the task of measurement with descriptive/causal modelling, although in practice most applied structural equation modelling is quite naive with respect to the difficulty of making compelling causal claims.
Alvarez, Mike, José Antonio Cheibub, Fernando Limongi, and Adam Przeworski. 1996. “Classifying Political Regimes.” Studies in Comparative International Development 31 (2): 3–36.
Bartholomew, David J, M Knott, and Irini Moustaki. 2011. Latent Variable Models and Factor Analysis : A Unified Approach. 3rd ed. / David Bartholomew, Martin Knott, Irini Moustaki. Wiley Series in Probability and Statistics. Hoboken, N.J.: Wiley.
Bartholomew, David J, Fiona Steele, Jane Galbraith, and Irini Moustaki. 2008. Analysis of Multivariate Social Science Data. Chapman; Hall/CRC.
Blalock, Hubert M. 1982. Conceptualization and Measurement in the Social Sciences. 04; H61, B5.
Everitt, Brian, and Torsten Hothorn. 2011. An Introduction to Applied Multivariate Analysis with r. Springer Science & Business Media.
Hanretty, Chris. 2017. “Areal Interpolation and the UK’s Referendum on EU Membership.” Journal of Elections, Public Opinion and Parties 27 (4): 466–83.
James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning. Vol. 112. Springer.
Pemstein, Daniel, Stephen A Meserve, and James Melton. 2010. “Democratic Compromise: A Latent Variable Analysis of Ten Measures of Regime Type.” Political Analysis 18 (4): 426–49.
World Bank. 2018. “The Human Capital Project.” International Bank for Reconstruction and Development / World Bank.
Zucco Jr, Cesar, Mariana Batista, and Timothy J Power. 2019. “Measuring Portfolio Salience Using the Bradley–Terry Model: An Illustration with Data from Brazil.” Research & Politics 6 (1): 2053168019832089.