The author defines the concept of identification and explains what 'goes wrong' with some nonrecursive models to make them nonidentified. He provides various tests which can be used to determine whether a nonrecursive model is identified, and reviews common techniques for estimating the parameters of an identified model.

Nonrecursive Models provides explicit guidance to researchers on the estimation and assessment of nonrecursive simultaneous equation models in a clear, condensed and precise form. It guides readers through the specification and identification of simultaneous equation models, how to assess the quality of the estimates, and how to correctly interpret results.

Nonrecursive Models is a clear and concise introduction to the estimation and assessment of nonrecursive simultaneous equation models. This unique monograph gives practical advice on the specification and identification of simultaneous equation models, how to assess the quality of the estimates, and how to correctly interpret results.

This book has been replaced by Principles and Practice of Structural Equation Modeling, Fifth Edition, ISBN 978-1-4625-5191-0.

This edited volume gives a new and integrated introduction to item response models (predominantly used in measurement applications in psychology, education, and other social science areas) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. It also includes a chapter on the statistical background and one on useful software.

With the availability of software programs, such as LISREL, EQS, and AMOS, modelling (SEM) techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and test for the plausibility of the hypothesizing for a particular data set. However, the popularity of these techniques has often led to misunderstandings of them and even their misuse, particularly by students exposed to them for the first time. Through the use of careful narrative explanation, Maruyama's text describes the logic underlying SEM approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores the various methodologies for analyzing structural equation data. In addition, Maruyama provides carefully constructed exercises both within and at the end of chapters.

This book develops a nonstandard approach to control systems analysis and design, exploring the properties of a new type of model called non-recursive behavioural models, unlike the recursive behavioural models of classical state space representation. For a real plant exhibiting a linear behaviour in the vicinity of any operating point, a non-recursive behavioural model (associated with an operating point) is defined as a coherent collection of appropriately selected input-state transfers, where, for a given timeline, the plant is actuated by piecewise constant input vectors. This work successively presents: mathematical preliminaries, definitions of linear non-recursive behavioural models, techniques for state controllability analysis, procedures for feedback control and optimal control design. All theoretical results are illustrated by laboratory experiments. This monograph is useful for postgraduate students, research workers and practitioners interested in systems theory and its applications.