Analysis of complex surveys
Author(s)
Bibliographic Information
Analysis of complex surveys
(Wiley series in probability and mathematical statistics, . Applied probability and statistics)
Wiley, c1989
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Note
Bibliography: p. [291]-301
Includes index
Description and Table of Contents
Description
Sample surveys form the most widely used method of collecting quantitative social data and offer extensive opportunities for analyzing social phenomena. However, the direct application of standard methods of statistical analysis, devised historically within different traditions of data collection such as experimentation, may be inappropriate and misleading. This volume discusses appropriate principles and methods for the analysis of surveys, such as stratified multi-stage sampling, as well as the complex structure of the populations upon which these designs are based. It thus provides a complement to standard books on methods of statistical analysis, such as contingency table analysis, regression analysis or multivariate analysis for researchers who wish to apply these methods to survey data. The volume will be of interest to statisticians, government, social and market researchers, sociologists, economists, epidemiologists, political scientists, educationalists and graduate students.
Table of Contents
- Part 1 Aggregated analysis - standard errors and significance tests: introduction, C.J.Skinner
- domain means, regression and multivariate analysis, C.J.Skinner
- chi-squared tests for contigency tables, J.N.K.Rao and D.R.Thomas
- measures of association for contingency tables, E.A.Molina. Part 2 Aggregated analysis - point estimation and bias: introduction, T.M.F.Smith
- the effect of selection of regression analysis, G.Nathan and T.M.F.Smith
- multivariate analysis, T.M.F.Smith and D.J.Holmes
- selection based on the response variable in logistic regression, A.J.Scott and C.J.Wild. Part 3 Disaggregated analysis - modelling structured populations: introduction, D.Holt
- multilevel and multivariate models in survey analysis, H.Goldstein and R.Silver
- regression models for stratified multistage cluster samples, D.Pfeefferman and L.LaVange
- logistic models for contingency tables, D.Holt and P.D.Ewings.
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