This is a comprehensive introduction to configural frequency analysis, its rationale, and various modifications. When more individuals than expected display a pattern of characteristics, these individuals belong to a type. When fewer individuals than expected display a pattern they belong to an antitype. This book deals with methods that focus on groups of subjects in contingency tables. A many-faceted statistical method, CFA is useful whenever categorical variables are analyzed. The original contribution of this text is the linking of CFA to log-linear modeling and the general linear model, enabling the reader to relate CFA to a well-known statistical background.

This unique book provides a comprehensive and detailed coverage of configural frequency analysis (CFA), the most useful method of analysis of categorical data in person-oriented research. It presents the foundations, methods, and models of CFA and features numerous empirical data examples from a range of disciplines that can be reproduced by the readers. It also addresses computer applications, including relevant R packages and modules. Configural frequency analysis is a statistical method that allows the processing of important and interesting questions in categorical data. The perspective of CFA differs from the usual perspective of relations among variables; its focus is on patterns of variable categories that stand out with respect to specific hypotheses, and as such, CFA allows for testing numerous substantive hypotheses. The book describes the origins of CFA and their relation to chi-square analysis as well as the developments that are based on log-linear modeling. The models covered range from simple models of variable independence to complex models that are needed when causal hypotheses are tested. Empirical data examples are provided for each model. New models are introduced for person-oriented mediation analysis and locally optimized time series analysis, and new results concerning the characteristics of CFA methods are bolstered using Monte Carlo simulations. Primarily intended for researchers and students in the social and behavioral sciences, the book will also appeal to anyone who deals with categorical data from a person-centered perspective.

Using real-world data examples, this authoritative book shows how to use the latest configural frequency analysis (CFA) techniques to analyze categorical data. Some of the techniques are presented here for the first time. In contrast to methods that focus on relationships among variables, such as log-linear modeling, CFA allows researchers to evaluate differences and change at the level of individual cells in a table. Illustrated are ways to identify and test for cell configurations that are either consistent with or contrary to hypothesized patterns (the types and antitypes of CFA); control for potential covariates that might influence observed results; develop innovative prediction models; address questions of moderation and mediation; and analyze intensive longitudinal data. The book also describes free software applications for executing CFA.

Traditionally, developmental psychology has its focus on individuals. Developmentalists aim to describe regularities in individuals' change and development across time, to explain the processes and mechanisms that are involved in producing change and regularity, and eventually, to design strategies for optimization and modification of developmental pathways. Although the role of contexts has always been of central concern for these purposes, it is nevertheless quite surprising to note that compared to the effort devoted to individuals, relatively little attention has been paid to the study of the nature and organization of their contexts. This volume is an exploration of the idea that how we describe and explain human development will be closely tied to our understanding of what contexts are, how individuals and contexts become influential for one another, what contexts do to and with individuals, and how contexts and their influences change themselves across time. A major theme is whether the traditional dichotomy between individuals and their contexts may be artificial, perhaps culturally biased, and after psychologists have adhered to it for about a century, may have become an impediment to increasing our understanding of developmental processes. With this volume, the editors contribute a serious consideration of development and systematic change to emerging models of person-context relations, and provide suggestions about how it may be possible to incorporate these notions in developmental research and theorizing.

Developmental Psychopathology, Second Edition, contains in three volumes the most complete and current research on every aspect of developmental psychopathology. This seminal reference work features contributions from national and international expert researchers and clinicians who bring together an array of interdisciplinary work to ascertain how multiple levels of analysis may influence individual differences, the continuity or discontinuity of patterns and the pathways by which the same developmental outcomes may be achieved. This volume addresses theoretical perspectives and methodological issues, including cross-cultural perspectives, developmental epidemiology, self determination theory, and gender issues.

The subject of this book is the incorporation and integration of mathematical and statistical techniques and information science topics into the field of classification, data analysis, and knowledge organization. Readers will find survey papers as well as research papers and reports on newest results. The papers are a combination of theoretical issues and applications in special fields: Spatial Data Analysis, Economics, Medicine, Biology, and Linguistics.

Longitudinal research is a broad field in which substantial advances have been made over the past decade. Unlike many of the existing books that only address the analysis of information. The Handbook of Longitudinal Research covers design and measurement as well as the data analysis. Designed for use by a wide-ranging audience, this Handbook not only includes perspective on the methodological and data analysis problems in longitudinal research but it also includes contributors' data sets that enable readers who lack sophisticated statistics skills to move from theories about longitudinal data into practice. As the comprehensive reference, this Handbook has no direct competition as most books in this subject area are more narrowly specialized and are pitched at a high mathematical level. Contributors and subject areas are interdisciplinary to reach the broadest possible audience (i.e., psychology, epidemiology, and economics research fields) Summary material will be included for less sohisticated readers Extensive coverage is provided of traditional advanced topics