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Advanced Statistical Techniques in Sociology: A Detailed Exploration

Delve into advanced statistical tools such as Multiple Correspondence Analysis and Multinomial Logistic Regression, crucial for social research. Learn how these methods can unveil intricate patterns and associations within complex data sets. Explore the application of multi-level models and specialized software for in-depth analysis. Discover insights from renowned theorists like Pierre Bourdieu and practical examples from research studies. Enhance your statistical proficiency and understanding of sociological phenomena with this comprehensive guide.

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Advanced Statistical Techniques in Sociology: A Detailed Exploration

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  1. University of Warwick, Department of Sociology, 2012/13SO 201: SSAASS (Surveys and Statistics) (Richard Lampard)A glimpse beyond the module…(Week 20)

  2. Multiple Correspondence Analysis • This isn’t exactly a straightforward extension of basic correspondence analysis, but it does allow information from multiple cross-tabulations to be pulled together to ‘unpack’ a mapping common to these. (See Chapter 7 of Cox, T.F. 2005. An Introduction to Multivariate Analysis. London: Hodder Arnold.) • It has been used extensively by the French social theorist Pierre Bourdieu, notably in his 1984 book Distinction. • See also Harrits, G.S. 2013. ‘Class, culture and politics: on the relevance of a Bourdieusian concept of class in political sociology’, Sociological Review 61.1: 172-202.

  3. Multi-level models • These models are used when there are units of analysis at two levels, e.g. pupils within schools. • However, sometimes the ‘higher’ level unit of analysis is a ‘nuisance’ level, e.g. where a sample of addresses is drawn from a sample of areas

  4. Software! • MLMs are not a feature of SPSS version 21. • Researchers use more flexible and/or specialised software such as MLwiN. Example Khattab, N., Johnston, R., Sirkeci, I. and Modood, T. 2012. ‘Returns on education amongst men in England and Wales: The impact of residential segregation and ethno-religious background’, Research in Social Stratification and Mobility 30.3: 296-309.

  5. Multinomial logistic regression • In many ways this is a straightforward extension of logistic regression. • The dependent variable has three or more categories, with one of these acting as the reference category. • An alternative is to break the analysis down into binary logistic regressions.

  6. Software again! • Multinomial logistic regressions can be fitted using SPSS (see Chapter 15 of Gray, C.D. and Kinnear, P. 2012. IBM SPSS Statistics 19 Made Simple. New York: Psychology Press.)

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