The Secondary Analysis of Survey Data (Sage Benchmarks in Social Research Methods)

The Secondary Analysis of Survey Data (Sage Benchmarks in Social Research Methods)

By: Martin I. A. Bulmer (editor), Nick Allum (editor), Patrick Sturgis (editor)Hardback

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This collection brings together the key publications on the secondary analysis of data and embraces many aspects of how to analyse quantitative survey data, whether primary or secondary. As secondary analysis, defined as use of data that was collected by individuals other than the investigator, is often a starting point for other social science research methods, this set will be a critical resource for researchers across the social sciences. Volume 1 introduces secondary analysis and explores the sources and types of survey data available, research design, causality and different approaches to analysis. Volume 2 centres on exploring and describing data, measurement in surveys, inference and other issues that arise in data analysis. Volume 3 concerns the general linear model, models for categorical data, classification and typology construction and latent variable models and Volume 4 presents structural equation modelling, multilevel modelling and longitudinal analysis.

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About Author

Nick Allum is Professor of Sociology at the University of Essex, with expertise in survey design and analysis, public understanding of science, social and political trust and risk perception. He has published widely in these areas and is a regular advisor to government and 3rd sector partners on large-scale research projects in the area of public understanding of science and survey research more generally. He teaches statistical methods, directs the MSc in Survey Methods for Social Research at Essex and specialises in latent variable and structural equation modelling. Nick has been academic advisor for several major UK surveys, including the Wellcome Trust Monitor and the Dept of Business Industry and Skills (BIS) Public Attitudes to Science Survey as well as advising the US National Science Board on several science surveys. Nick is currently General Secretary of the European Survey Research Association.


Volume 1: Issues in the Analysis of Survey Data Introduction to the four volumes - Martin Bulmer, Patrick Sturgis and Nick Allum Introduction to Volume One of the set - Martin Bulmer Secondary Analysis and Sharing Data Using social science data archives - Morris Rosenberg An introduction to secondary analysis - Angela Dale, Sara Arber and Mike Procter Sharing research data in the social sciences - Jerome M Clubb et al Toward cumulative knowledge: theoretical and methodological issues - Stephen E Fienberg et al Issues in Research Design Some observations on study design - S A Stouffer Durkheim's SUICIDE and the problems of empirical research - Hannan C Selvin Longitudinal v cross-sectional methods for behavioural research: a first round knock-out - R B Davies and A R Pickles Causality and Causal Order Some statistical aspects of causality - D R Coxand and N Wermuth The quantitative analysis of large-scale data-sets and rational action theory: for a sociological alliance - J H Goldthorpe Rethinking Causality - S Lieberson Causality: production and propagation - Wesley C Salmon Causal order - T Hirschi and H C Selvin Elaboration Test factor standardization as a method of interpretation - Morris Rosenberg Attitudes, behavior and the intervening variables - Howard Ehrlich The logical structure of suppressor variables - Morris Rosenberg, Morris Elaborating the association between variables - Mervin Susser Analytic Issues Ecological correlations and the behavior of individuals. - W S Robinson Replication, replication - Gary King Quality issues with survey research - Angela Dale Divorce effects' and causality in the social sciences - Maire NiBhrolchain Volume 2: Measurement and Inference Issues in Survey Measurement On the theory of scales of measurement - S S Stevens Factor scaling, external consistency and the measurement of theoretical constructs - R A Zeller and E G Carmines A simple theory of the survey response: Answering questions versus revealing preferences. - J Zaller and S Feldman Samples, Inference and Error History and development of the theoretical foundations of survey based estimation and analysis - J N K Rao and D R Bellhouse Variance estimation for complex estimators in sample surveys - K Rust A 'super-population viewpoint' for finite population sampling - H O Hartley R L Sielken Jr. Statistics and causal inference - P Holland Weighting methods - G Kalton and I Flores-Cervantes Sampling weights and regression analysis - C Winship and L Radbill Inference under Complex Sample Designs Inference with survey weights - R J A Little Inference from complex samples - L Kish and M R Frankel Analysing complex survey data: Clustering, stratification and weights - P Sturgis Missing data in large surveys - R Little Analyzing incomplete political science data: An alternative algorithm for multiple imputation - G King, et al Volume 3: Summarizing and Modelling Survey Data Exploratory Data Analysis Summarizing distributions - Melissa Hardy How to display data badly - Howard Wainer Cluster analysis - D Bartholomew et al Correspondence Analysis: Graphical Representation of Categorical Data in Marketing Research - Donna Hoffman and George Franke Linear and Non-linear Regression The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations - R M Baron and D A Kenny In defense of multiplicative terms in multiple regression equations - R J Friedrich How Not to Lie with Statistics: Avoiding Common Mistakes in Quantitative Political Science - G King A Tutorial in Logistic Regression - Alfred DeMaris Loglinear Models: A Way to Study Main Effects and Interactions for Multidimensional Contingency Tables With Categorical Data - Leonard Marascuilo and Patricia Busk Latent Variable Models Latent variables in psychology and the social sciences - Kenneth Bollen Component analysis versus common factor analysis: Some issues in selecting an appropriate procedure - W F Velicer and D N Jackson Confirmatory factor analysis - D L Bandalos Measurement invariance, factor analysis and factorial invariance - W Meredith Volume 4: Simultaneous Equations, Hierarchical and Longitudinal Models Structural Equation Models The decomposition of effects in path analysis - Duane F Alwin and Robert M Hauser A general method for estimating a linear structural equation system - Karl G Joreskog Principles and practice in reporting structural equation analyses - R P McDonald and M H Ring Ho Hierarchical Data Structures: Multilevel and Longitudinal Analysis Multilevel modelling of survey data - Harvey Goldstein Modeling multilevel data structures - M R Steenbergen and B S Jones Context, composition and heterogeneity: using multilevel models in health research - C Duncan and G Moon Multilevel models for repeated binary outcomes: attitudes and voting over the electoral cycle - M Yang, H Goldstein and A Heath A didactic example of multilevel structural equation modelling applicable to the study of organisations - D Kaplan and P R Elliot Using panel data to estimate the effect of events - Paul Allison Panel Models in Sociological Research: Theory into Practice - Charles Halaby, Charles Myths and methods: "Myths about longitudinal research" plus supplemental questions. - D R Rogosa Cohort analysts' futile quest: statistical attempts to separate age, period and cohort effects - David Glenn Changing attitudes towards pre-marital sex: cohort, period and ageing effects - D Harding and C Jencks Latent curve analysis - W Meredith and J Tisak General longitudinal modeling of individual differences in experimental designs: A latent variable framework for analysis and power estimation - Bengt Muthen and Patrick Curran Application of hierarchical linear models to assessing change - A S Bryk and S W Raudenbush Using covariance structure analysis to detect correlates and predictors of change - J B Willett and A Sayer

Product Details

  • publication date: 18/02/2009
  • ISBN13: 9781412903844
  • Format: Hardback
  • Number Of Pages: 1664
  • ID: 9781412903844
  • ISBN10: 141290384X

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