Addresses basic aspects of research design which are central and common to many related fields in the social sciences, in the health sciences, in education and in market research. Presents a unified approach to a common core of problems of statistical design that exists in all these fields, along with basic similarities in practical solutions. Describes many examples and analogies that are 'portable' from field to field of applications. Deals with designs that are the primary basis of research studies, but are neglected in most statistical textbooks (which tend to concentrate on statistical analysis).
1. Representation, Randomization and Realism.
1.1 Three Criteria.
1.2 Four Classes of Variables.
1.3 Surveys, Experiments, and Controlled Investigations.
1.4 Randomization of Subjects over Treatments and Over Populations.
1.5 Statistical Tests.
1.6 An Ordered List of Research Designs.
1.7 Representation and Probability Sampling.
1.8 Model-Dependent Inference.
2. Analytical Use of Sample Surveys.
2.1 Populations of Elements and Sampling Units.
2.2 Inferences from Complex Samples.
2.3 Domains and Subclasses: Classifications.
2.4 Overview of Subclass Effects.
2.5 Proportionate Stratified Element Sampling (PRES).
2.6 Cluster Sampling.
2.7 Four Obstacles to Representation in Analytic Studies.
3. Designs for Comparisons.
3.1 Substitutes for Probability Sampling.
3.2 Basic Modules for Comparisons.
3.3 Four Modules: Costs, Variances, Bias Sources.
3.4 Five Basic Designs for Comparisons.
3.5 Classification for 22 Sources of Bias.
3.6 Time Curves of Responses.
3.7 Evaluation Research.
4. Controls for Disturbing Variables.
4.1 Control Strategies.
4.2 Analysis in Separate Subclasses.
4.3 Selecting Matched Units.
4.4 Matched Subclasses.
4.5 Standardization: Adjustment by Weighting Indexes.
4.6 Covariances and Residuals from Linear Regressions; Categorical Data Analyses.
4.7 Ratio Estimates.
5. Samples and Censuses.
5.1 Censuses and Researchers.
5.2 Samples Compared to Censuses.
5.3 Samples Attached to Censuses.
6. Sample Designs over Time.
6.1 Technology and Concepts.
6.2 Purposes and Designs for Periodic Samples.
6.3 Changing and Mobile Populations.
6.4 Panel Effects.
6.5 Split-Panel Designs.
6.6 Cumulating Cases and Combining Statistics from Samples.
7. Several Distinct Problems of Design.
7.1 Analytical Statistics from Complex Samples.
7.2 Generalizations beyond the Modules of 3.3.
7.3 Multipurpose Designs.
7.4 Weighted Means: Selection, Bias, Variance.
7.5 Observational Units of Variable Sizes.
7.6 On Falsifiability in Statistical Design.
The current cloth edition is now being converted into a paperback format, at a reduced price. For use as a reference and /or textbook.
Leslie Kish was a Professor at the Institute for Social Research at the University of Michigan. He was President of the American Statistical Association in 1977 and was a Fellow of the Royal Statistical Society and the American Academy of Arts and Sciences.