内容説明
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.
目次
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 Joereskog
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
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