The dual objectives of this thesis are to assess the merits of certain statistical methods as applied to sociological data and to use statistical methods to produce interesting and worthwhile substantive results. The main statistical focus of the thesis is the analysis of two-way tables, for which purpose association models and correspondence analysis are used. Some of the tables analysed require the application of quasi-association models and association models with more than one dimension. Elsewhere in the thesis a proportional hazards model and various log-linear models are fitted. The substantive focus of the thesis is the relationship between marital formation/dissolution and social stratification in modern Britain. Particular attention is paid to assortative marriage for social status, with the relationships between spouses' occupations, educational levels and social origins being considered in detail. Assortative marriage for religion and for party political identification/voting intention are also examined. The data analysed come from a variety of social surveys, including both government surveys (e.g. various General Household Surveys, and the Family Formation Survey) and academic surveys (e.g. the Oxford Mobility Survey and the Social Change and Economic Life Initiative survey). The thesis conclusively demonstrates the utility of association models, log-linear models and proportional hazards models as applied to data relating to marital formation/dissolution. Among the numerous substantive findings are that there was a significant post-war decline in the strength of the relationship between spouses' social origins, and that unemployment appears to cause an increase in the risk of marital dissolution.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:481774 |
| Date | January 1992 |
| Creators | Lampard, Richard James |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:fb961361-18b3-4801-bd83-8d2bc5b234d5 |
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