A First Course in Structural Equation Modeling, 2nd edition by Tenko Raykov, George A. Marcoulides

By Tenko Raykov, George A. Marcoulides

During this ebook, authors Tenko Raykov and George A. Marcoulides introduce scholars to the fundamentals of structural equation modeling (SEM) via a conceptual, nonmathematical procedure. For ease of knowing, the few mathematical formulation offered are utilized in a conceptual or illustrative nature, instead of a computational one. that includes examples from EQS, LISREL, and Mplus, a primary path in Structural Equation Modeling is a wonderful beginner’s advisor to studying how one can arrange enter documents to slot the main universal kinds of structural equation versions with those courses. the fundamental rules and techniques for undertaking SEM are self reliant of any specific software program. Highlights of the second one version comprise: • evaluation of latent swap (growth) research types at an introductory point • assurance of the preferred Mplus application • up to date examples of LISREL and EQS • A CD that includes all the text’s LISREL, EQS, and Mplus examples. a primary path in Structural Equation Modeling is meant as an introductory publication for college kids and researchers in psychology, schooling, company, drugs, and different utilized social, behavioral, and health and wellbeing sciences with constrained or no past publicity to SEM. A prerequisite of uncomplicated data via regression research is usually recommended. The booklet often attracts parallels among SEM and regression, making this previous wisdom worthwhile.

Show description

Read Online or Download A First Course in Structural Equation Modeling, 2nd edition PDF

Similar mathematics books

Out of the Labyrinth: Setting Mathematics Free

Who hasn't feared the maths Minotaur in its labyrinth of abstractions? Now, in Out of the Labyrinth, Robert and Ellen Kaplan--the founders of the mathematics Circle, the preferred studying application began at Harvard in 1994--reveal the secrets and techniques at the back of their hugely winning process, best readers out of the labyrinth and into the joyous include of arithmetic.

An Introduction to Laplace Transforms and Fourier Series (2nd Edition) (Springer Undergraduate Mathematics Series)

Laplace transforms remain a crucial instrument for the engineer, physicist and utilized mathematician. also they are now helpful to monetary, financial and organic modellers as those disciplines turn into extra quantitative. Any challenge that has underlying linearity and with resolution in keeping with preliminary values might be expressed as a suitable differential equation and as a result be solved utilizing Laplace transforms.

From combinatorics to dynamical systems: journées de calcul formel, Strasbourg, March 22-23, 2002

This quantity includes 9 refereed learn papers in quite a few parts from combinatorics to dynamical platforms, with machine algebra as an underlying and unifying subject. subject matters lined comprise abnormal connections, rank relief and summability of suggestions of differential platforms, asymptotic behaviour of divergent sequence, integrability of Hamiltonian platforms, a number of zeta values, quasi-polynomial formalism, Padé approximants regarding analytic integrability, hybrid platforms.

Factorization of Matrix and Operator Functions - The State Space Method

This booklet delineates many of the sorts of factorization difficulties for matrix and operator services. the issues originate from, or are stimulated via, the idea of non-selfadjoint operators, the speculation of matrix polynomials, mathematical platforms and keep watch over conception, the speculation of Riccati equations, inversion of convolution operators, and the speculation of task scheduling in operations learn.

Extra info for A First Course in Structural Equation Modeling, 2nd edition

Example text

Although it may happen that multivariate normality holds when all observed variables are individually normally distributed, it is desirable to also examine bivariate normality that is generally not a consequence of univariate normality. In fact, if the observations are from a multivariate normal distribution, each bivariate distribution should also be normal, like each univariate distribution. , Tabachnik & Fidell, 2001). , Johnson & Wichern, 2002; Khattree & Naik, 1999; Marcoulides & Hershberger, 1997).

In fact, unless its metric is defined, the scale of the latent variable will remain indeterminate. Subsequently, this will lead to model-estimation problems and unidentified parameters and models (discussed later in this chapter). For any independent latent variable included in a given model, the metric can be fixed in one of two ways that are equivalent for this purpose. Either its variance is set equal to a constant, usually 1, or a path going out of the latent variable is set to a constant (typically 1).

Conversely, a researcher may elect to free some initially fixed parameters, rendering them free parameters, after making sure of course that the model remains identified (see below). The third type of parameters are called constrained parameters, also sometimes referred to as restricted or restrained parameters. Constrained parameters are those that are postulated to be equal to one another—but their value is not specified in advance as is that of fixed parameters—or involved in a more complex relationship among themselves.

Download PDF sample

Rated 4.18 of 5 – based on 8 votes