The Secondary Analysis of Survey Data

Four Volume Set
ISBN: 978-1-4129-0384-4
Verlag: SAGE PUBN

Buch, Englisch, 1664 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 3385 g

Reihe: Sage Benchmarks in Social Rese

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.

Autoren/Hrsg.

Bulmer, Martin I. a.

Sturgis, Patrick

Allum, Nick

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Wirtschafts- und Sozialwissenschaften

Inhaltsverzeichnis

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

Über Autor(innen)

Allum, Nick
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.