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A large amount of data that is considered within sociological studies consists of categorical variables that lend themselves to tabular analysis. In the sociological analysis of data regarding social class and educational attainment, for example, the variables of interest can often plausibly be considered as having a substantively interesting order. Standard log-linear models do not take ordinality into account, thereby potentially they may disregard useful information. Analyzing tables where the response variable has ordered categories through model building has been problematic in software packages such as GLIM (Aitken et al., 1989). Recent developments in statistical modelling have offered new possibilities and this paper explores one option, namely the continuation ratio model which was initially reported by Fienberg and Mason (1979). The fitting of this model to data in tabular form is possible in GLIM although not especially trivial and by and large this approach has not been employed in sociological research. In this paper I outline the continuation ratio model and comment upon how it can be fitted to data by sociologists using the GLIM software. In addition I present a short description of the relative merits of such an approach. Presenting this paper in an electronic format facilitates the possibility of replicating the analysis. The data is appended to the paper in the appropriate format along with a copy of the GLIM transcript. A dumped GLIM4 file is also attached.

Developing Internet Based Teaching and Learning Resources for Social Sciences: A CSCW approach

Cover Page -- Title Page -- Copyright Page -- Contents -- List of Figures -- List of Tables -- List of Contributors -- 1 Introduction -- PART I: MEASURING SOCIAL STRATIFICATION -- 2 Stratification Research and Occupation-Based Social Classifications -- 3 Measures and Dimensions of Occupational Stratification: The Case of a Relational Scale for Italy -- 4 A Relational Occupational Scale for Russia -- PART II: SOCIAL STRATIFICATION OVER THE LIFE COURSE -- 5 Cumulative Inequalities Along the Life Course: Long-Term Trends in the German Labour Market -- 6 Family Background and the Life Cycle Effects of Father's Class and Income -- 7 Social Stratification and Cognitive Ability: An Assessment of the Influence of Childhood Ability Test Scores and Family Background on Occupational Position Across the Lifespan -- 8 Intergenerational and Intragenerational Social Mobility in Britain -- PART III: DEMOGRAPHIC, INSTITUTIONAL AND SOCIO-ECONOMIC CHANGES -- 9 Ethnicity and Skilled Work in the United States -- 10 Occupation and Pay Across the Generations: The Labour Market Experience of Four Ethno-Religious Groups in Britain -- 11 The Labour Market Earnings of Minority Ethnic Groups in Great Britain and the USA (1990-2000) -- 12 The Relationship Between Social Stratification and First Birth in Scotland -- 13 Stratification, Work and Early Parenthood -- 14 Labour Market Returns to Tertiary Education in Post-Socialist Countries -- PART IV: POLITICAL AND POLICY RESPONSES TO STRATIFICATION -- 15 Labouring Under a Misapprehension: Politicians' Perceptions and the Realities of Structural Social Mobility in Britain, 1995-2010 -- 16 Security or Equality? The Difficult Reform of the Italian Welfare State

"First published as What is Quantitative Longitudinal Data Analysis?, this title is now available as part of the Bloomsbury Research Methods series. This book provides a practical and up-to-date introduction to influential approaches to quantitative longitudinal data analysis in the social sciences. It discusses definitions and terms, explains the relative attractions of such a design and enumerates, in an accessible way, the main techniques of analysis, explaining their requirements, statistical properties and their substantive contributions"--

Cover -- Half-Title -- Series -- Title -- Contents -- List of figures -- List of tables -- Preface -- Series editor's foreword -- Acknowledgements -- 1 Introduction to quantitative longitudinal data -- Introduction -- Cross-sectional social surveys -- Longitudinal social surveys with repeated contacts -- Modes of survey data collection -- The Research value of repeated contacts quantitative longitudinal data -- Micro-level dynamics -- Temporal ordering of events -- Residual heterogeneity -- State dependence -- Age, period and cohort effects -- Conclusions -- 2 Quantitative longitudinal datasets -- Large-scale panel studies -- The British Household Panel Survey -- UK Household Longitudinal Study - Understanding society -- Cohort studies -- The major British cohort studies -- Other British birth cohort studies -- Other longitudinal studies -- Cross-national and comparative longitudinal studies -- Conclusions -- 3 Temporal analysis with cross-sectional data -- Introduction -- Comparing survey measures -- An example of analysing pooled cross-sectional surveys -- Cross-national comparative research using repeated cross-sectional surveys -- Conclusions -- 4 The analysis of duration data -- Introduction -- Measuring durations -- Duration models -- Parametric duration models -- Competing risk models -- Discrete-time models -- Conclusions -- 5 The analysis of repeated contacts data -- Introduction -- Approaches to analysing panel data: Part 1 -- Approaches to analysing panel data: Part 2 -- Comparing different panel models: Example 1 -- Comparing different panel models: Example 2 -- Comparing fixed effects panel models and random effects panel models -- Panel models for binary outcomes -- Panel models with other outcomes -- Dynamic panel models -- Estimating random effects models in Stata -- Conclusions.

Abstract
This paper contributes to the sociological understanding of social class inequalities in childhood similarities test scores. We undertake a comparative analysis of two cohorts of British children born 30 years apart. There is a similar negative relationship in both cohorts. Children born in families in the less advantaged social classes have lower childhood similarities test scores. This is consequential because these children enter secondary school with restricted capabilities in logical thinking, concept formation and abstract reasoning.

This paper examines the roles of parental social class and cultural capital in inequalities in English school qualifications. The analytical focus is the General Certificate of Secondary Education (GCSE). Integral to Bourdieu's theory of cultural reproduction is the conception that inequalities in cultural capital explain the unequal scholastic achievements of pupils from different social class backgrounds. This paper is a novel investigation using data from Understanding Society and linked administrative education records from the National Pupil Database. The central empirical findings do not support the Bourdiuesian position, and there is no evidence that the substantial parental social class inequalities that are observed in school GCSE outcomes can be explained by inequalities in cultural capital. Engagement in reading related activities are mildly influential, but engagement in highbrow cultural activities are not influential. This is an important finding as the concept of cultural capital has become more prominent in Government education policy.

In this video, Vernon Gayle is in conversation with Graham Crow, Professor of Sociology and Methodology at the School of Social and Political Science, University of Edinburgh. As he approaches retirement, Graham reflects on his career, including studying sociology, his experiences of communities research, and methods used in disability research. Graham also explores innovations in research and his works with the National Centre for Research Methods (NCRM).

Politicians regularly make statements to the effect that there are two, three or even four generations, within the same family, that have never worked. Politicians are also on record as stating that there is a something for nothing culture. These concepts of generations and cultures of worklessness regularly appear in the traditional print media, internationally and in academia. Where the reasons for holding a belief are adequate and the belief formed from the available evidence is adequate, the belief may be understood as properly held. Where this is not the case the belief is improperly held. This paper uses the British Household Panel Survey to link information on individuals and between generations to assess whether belief in generations and cultures of worklessness are 'properly held'. The level of intergenerational worklessness is quantified and the circiumstances of those out of work assessed. The descriptive analysis confirms previous research which finds no evidence for the generations and cultures theses. In the absence of corroborating evidence it is argued that the concepts of generations and cultures of worklessness should be treated as improperly held beliefs and it is time they are done away with.

PurposeThe purpose of this article is to explore whether the concept of social capital is helpful in explaining the educational underachievement of looked after children.Design/methodology/approachAnalysis of data on educational achievement and social care in a cohort of 1,407 children over the age of 15 who left care in two Scottish local authorities between 2000 and 2005.FindingsThe educational attainments of children do reflect key factors in their backgrounds before entry to care but their characteristics also lead them to be placed in specific placements that have differing abilities for promoting social capital. An examination of evidence on bonding social capital, bridging social capital, and linking social capital and trust, shows that social capital theory helps to theoretically interpret the low educational achievements of looked after children.Originality/valueThe large and comprehensive data set permits a factor analysis of background and care variables, thus clarifying the significance of each in explaining children's educational attainments and assessing the value of a social capital perspective.

ABSTRACTThis paper reports the findings of a research project which explored the care factors that influence the educational achievement of looked‐after children. The project was innovative because it focused on children looked after at home and away from home. A mixed‐methods strategy was adopted to analyse data from two large Scottish local authorities. The project developed, what is to date, the largest dataset which includes variables for one‐fifth of children discharged from care in Scotland over a 5‐year period. The qualitative element of the project collected in‐depth data on the care and education experiences of looked‐after children and care leavers.The overall finding was that looked‐after children perform less well academically than their counterparts in the general school population. The empirical data indicated that factors such as placement type, reason for becoming looked after and age on becoming looked after were significant in determining educational achievement. Empirical results further indicated that looked‐after children suffered from discrimination and social exclusion in many areas of their lives, including school and where they lived.

This article introduces a sociological audience to `quasi-variances' as a solution to the `reference category problem'.The reference category problem is associated with the interpretation of the effects of categorical explanatory variables within statistical models, and is especially relevant to sociological applications, where categorical explanatory variables are very common. This article presents a selection of examples (using multiple and logistic regression) to illustrate and comment on quasi-variance calculations for sociological models. In addition, the article is augmented with online materials provided by the authors, which aim to help social researchers practise and apply this technique using the popular data analysis software packages SPSS and Stata.The authors conclude that quasi-variance methods offer an attractive and practicable solution to the reference category problem that can, and should, be routinely operationalized by sociological researchers.