Abstract: Statistical methods covering log-linear models and latent-structure analysis are presented and described for the analysis of qualitative or categorical data to assist the pressing needs of social researchers and others in developing and applying a unified and systematic approach to the analysis of such data. The scope of applications in this approach includes methods for the sociologist examining the relationship between poverty and crime; the educational researcher examining the reliability and validity of a set of test items; the psychometrician developing a new measurement scale; the market researcher analyzing purchase behavior in different market segments; the medical researcher attempting to identify factors associated with various diseases (e.g., breast cancer); and the political scientist examining voter behavior. The methods are applicable to computer programs. (wz).

In recent years the loglinear model has become the dominant form of categorical data analysis as researchers have expanded it into new directions. This book shows researchers the applications of one of these new developments - how uniting ordinary loglinear analysis and latent class analysis into a general loglinear model with latent variables can result in a modified LISREL approach. This modified LISREL model will enable researchers to analyze categorical data in the same way that they have been able to use LISREL to analyze continuous data.

In this volume, leading researchers examine how latent variables can be incorporated in a variety of data-analysis strategies, such as structural equation modelling, regression analysis, log-linear modelling and prediction analysis. The contributors also discuss how latent variables analysis can be applied in developmental psychology research using methods such as cohort-time of measurement-age analysis, log-linear modelling of behaviour genetics hypothesis and analyses of repeatedly observed state measures. Detailed explanations of computations and software packages are included with each statistical method.

This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.

By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes. However, longitudinal research has many faces. This book examines all the main approaches as well as newer developments (such as structural equation modelling, multilevel modelling and optimal scaling) to enable the reader to gain a thorough understanding of the approach and make appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.

Categorical Variables in Developmental Research provides developmental researchers with the basic tools for understanding how to utilize categorical variables in their data analysis. Covering the measurement of individual differences in growth rates, the measurement of stage transitions, latent class and log-linear models, chi-square, and more, the book provides a means for developmental researchers to make use of categorical data. - Measurement and repeated observations of categorical data - Catastrophe theory - Latent class and log-linear models - Applications