Bücher der Reihe Quantitative Applications in the Social Sciences

Drawing on recent "event history" analytical methods from biostatistics, engineering and sociology, this book explains how longitudinal data can be used to study the causes of deaths, crimes, wars, and many other human-related events.

With empirical examples which are both plentiful and well chosen to teach the technique, this book provides a thorough guide to latent class scaling models for binary response variables.

This book provides a systematic and practical guide for researchers wishing to set up their own factorial survey design or to analyze factorial survey data.

An elementary introduction to significance testing, this paper provides a conceptual and logical basis for understanding these tests.

Describes the mathematical and logical foundations at a level that does not presume advanced mathematical or statistical skills. It illustrates how to do factor analysis with several of the more popular packaged computer programs.

Offers students a brief and accessible approach to systematically quantifying various types of narrative data they can collect during a research process.

This monograph is not statistical. It looks instead at pre-statistical assumptions about dependent variables and causal order. Professor Davis spells out the logical principles that underlie our ideas of causality and explains how to discover causal direction, irrespective of the statistical technique used. He stresses throughout that knowledge of the `real world'' is important and repeatedly challenges the myth that causal problems can be solved by statistical calculations alone.

Introduces the elements of experimental design and analysis. The text covers such topics as the fundamental concept of variability, hypothesis testing, how ANOVA can be extended to the multi-group situation and random designs.

These procedures, collectively known as discriminant analysis, allow a researcher to study the difference between two or more groups of objects with respect to several variables simultaneously, determining whether meaningful differences exist between the groups and identifying the discriminating power of each variable.

A review of the basic mathematical concepts that underlie most quantitative analysis in the social sciences is presented in this volume. The author begins with an algebra review featuring sets and combinations and then discusses limits and continuity. Calculus is presented next, with an introduction to differential calculus, multivariate functions, partial derivatives, and integral calculus. Finally the book deals with matrix algebra. Packed with helpful definitions, equations, examples and alternative notations, the book also includes a useful appendix of common mathematical symbols and Greek letters.

In this volume, Larry Toothaker provides the procedures that will enable researchers to establish the significance of differences between two comparable groups. Issues addressed include: planned versus post-hoc comparisons; step-by-step versus simultaneous test procedures; types of error rate; unequal sample sizes and variances; and interaction tests versus cell mean tests. Examples are used to illustrate major concepts.

Contains annotated samples of actual research questionnaires so that the reader can compare the usual paper questionnaire against the extra statements needed for clear computer-assisted interviewing. It also includes an overview of the important features to consider when buying a CADAC programme.

A comparison of three methods of metric scaling - correspondence analysis, principal components analysis and multiple dimensional preference scaling. This book focuses on the representation of the relations of variables and upon exploratory rather than predictive applications.

A guide to microcomputer 'usage' for social scientists that reflects the changes in systems, software and 'usage'. It includes material on: the Apple Macintosh system; the development of mainframe-quality statistical packages for micros; and, the development of Pascal and C as programming languages.

Focusing on situations in which analysis of variance (ANOVA) involving the repeated measurement of separate groups of individuals is needed, this book attempts to reveal the advantages, disadvantages and counterbalancing issues of repeated measures situations.

Recent advances in statistical methodology and computer automation are making canonical correlation analysis available to more and more researchers. This volume explains the basic features of this sophisticated technique in an essentially non-mathematical introduction which presents numerous examples. Thompson discusses the assumptions, logic, and significance testing procedures required by this analysis, noting trends in its use and some recently developed extensions.

A book which summarizes many of the recent advances in the theory and practice of achievement testing, in the light of technological developments, and developments in psychometric and psychological theory. It provides an introduction to the two major psychometric models, item response theory and generalizability theory, and assesses their strengths for different applications. The book closes with some speculations about the future of achievement tests for the assessment of individuals, as well as monitoring of educational progress.`...the book contains valuable information for both beginners and for advanced workers who want an overview of recent work in achievement testing.' -- The Journal of the American Statistical Association, June 1985

Secondary analysis has assumed a central position in social science research as existing survey data and statistical computing programmes have become increasingly available. This volume presents strategies for locating survey data and provides a comprehensive guide to US social science data archives, describing several major data files. The book also reviews research designs for secondary analysis.

A presentation and critique of the use of multiple measures of theoretical concepts for the assessment of validity (using the multi-trait multi-method matrix) and reliability (using multiple indicators with a path analytic framework).

Ordinal data can be rank ordered but not assumed to have equal distances between categories. Using support by judges for civil rights measures and bussing as the primary example, this paper indicates how such data can best be analyzed.

An advanced study which presumes a knowledge of multiple regression and factor analysis techniques, this paper considers two techniques for comparing entire sets of data, and develops the canonical correlation model as an extension of regression analysis in which there are several dependent variables.

Discusses basic concepts and methods associated with the application of operations research toward arriving at an optimum mix, level, or choice.

As budgets tighten and costs increase, it is becoming even more necessary that workable social programmes are shown to be worthy of support. This book presents one approach to evaluation -- multiattribute utility technology -- which stresses that evaluations should be comparative, and that all the different constituencies served by a programme and its different goals have to be kept in mind.

This volume shows how odds ratios can be used as a framework for understanding log-linear models. Moving systematically from the paradigmatic 2x2 case to more complicated cases, the author defines the odds ratio and demonstrates how it is a measure of association for tabular analysis.

Written in nontechnical language, this popular and practical volume has been completely updated to bring readers the latest advice on major issues involved in longitudinal research. It covers: research design strategies; methods of data collection; how longitudinal and cross-sectional research compares in terms of consistency and accuracy of results.

Outlines a set of techniques that enable a researcher to discuss the "hidden structure" of large data bases. These techniques use proximities, measures which indicate how similar or different objects are, to find a configuration of points which reflects the structure in the data.

A statistical method which will appeal to two groups in particular: those who are currently using the more traditional technique of exploratory factor analysis; and those who are interested in the analysis of covariance structures, commonly known as the LISREL model. The first group will find that this technique may be more appropriate to the analysis of their research problems; while the second group will find that confirmatory factor analysis is a useful first step to understanding the LISREL model, for this book, and its companion volume, Covariance Structure Models, are designed to be read consecutively. The proofs presented are simple, but the reader must feel comfortable with matrix algebra in order to understand the model.