Download e-book for iPad: A Beginner’s Guide to Structural Equation Modeling by Randall E. Schumacker, Richard G. Lomax
By Randall E. Schumacker, Richard G. Lomax
Noted for its crystal transparent causes, this ebook is taken into account the main complete introductory textual content to structural equation modeling (SEM). famous for its thorough evaluate of uncomplicated ideas and a wide selection of types, this booklet larger prepares readers to use SEM to various learn questions. Programming info and using algebra are stored to a minimal to assist readers simply take hold of the innovations to allow them to behavior their very own research and critique comparable learn. that includes a better emphasis on statistical strength and version validation than different texts, each one bankruptcy positive factors key innovations, examples from quite a few disciplines, tables and figures, a precis, and routines.
Highlights of the commonly revised 4th version include:
-Uses diversified SEM software program (not simply Lisrel) together with Amos, EQS, LISREL, Mplus, and R to illustrate applications.
-Detailed advent to the statistical tools with regards to SEM together with correlation, regression, and issue research to maximise realizing (Chs. 1 – 6).
-The five step method of modeling facts (specification, id, estimation, trying out, and amendment) is now coated in additional element and ahead of the modeling chapters to supply a extra coherent view of the way to create versions and interpret effects (ch. 7).
-More dialogue of speculation trying out, strength, sampling, influence sizes, and version healthy, severe themes for starting modelers (ch. 7).
- each one version bankruptcy now makes a speciality of one strategy to increase knowing by means of offering extra description, assumptions, and interpretation of effects, and an workout on the topic of research and output (Chs. eight -15).
-The use of SPSS AMOS diagrams to explain the theoretical models.
-The key positive aspects of every of the software program programs (Ch. 1).
-Guidelines for reporting SEM learn (Ch. 16).
-www.routledge.com/9781138811935 which supplies entry to facts units that may be used with any application, hyperlinks to different SEM examples, comparable readings, and magazine articles, and extra.
Reorganized, the hot version starts with a extra distinct advent to SEM together with a number of the software program applications on hand, via chapters on info access and modifying, and correlation that's serious to figuring out how lacking info, non-normality, dimension, and restrict of variety in rankings impacts SEM research. a number of regression, course, and issue versions are then reviewed and exploratory and confirmatory issue research is brought. those chapters reveal how saw variables percentage variance in defining a latent variables and introduce how dimension mistakes should be faraway from saw variables. bankruptcy 7 information the five SEM modeling steps together with version specification, identity, estimation, checking out, and amendment besides a dialogue of speculation checking out and the similar problems with strength, and pattern and impression sizes.Chapters eight to fifteen offer accomplished introductions to various SEM types together with a number of crew, Second-Order CFA, Dynamic issue, Multiple-Indicator Multiple-Cause, combined Variable and blend, Multi-Level, Latent progress, and SEM interplay types. all the five SEM modeling steps is defined for every version in addition to an software. bankruptcy routines supply perform with and improve realizing of the research of every version. The booklet concludes with a evaluation of SEM directions for reporting examine.
Designed for introductory graduate classes in structural equation modeling, issue research, complicated, multivariate, or utilized information, quantitative options, or facts II taught in psychology, schooling, company, and the social and healthcare sciences, this useful e-book additionally appeals to researchers in those disciplines. necessities contain an advent to intermediate data that covers correlation and regression principles.
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Additional info for A Beginner’s Guide to Structural Equation Modeling
In G. R. Hancock & R. O. ). Greenwich, CT: Information Age, pp. 493–519. , & Naugher, J. R. (2000). Outliers lie: An illustrative example of identifying outliers and applying robust methods. Multiple Linear Regression Viewpoints, 26(2), 2–6. Jöreskog, K. , & Sörbom, D. (1996). PRELIS2: User’s reference guide. Lincolnwood, IL: Scientific Software International. , & du Toit, M. (2001). LISREL8: New statistical features. Chicago, IL: Scientific Software International. McKnight, P. , McKnight, K. , & Aurelio, J.
All of the software is visual, interactive, comprehensive, and extensible. com/software/ LISREL: Stand-alone Software LISREL has evolved from a matrix-only software (LISREL9) to a simple set of syntax commands (SIMPLIS). You can obtain output in matrix format or obtain Introduction the basic results. The software comes with a free demo version, user guides, sets of data, and examples for the many different types of SEM models with a help menu to search for information and explanations of analysis and procedures.
Wright, S. (1918). On the nature of size factors. Genetics, 3, 367–374. Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20, 557–585. Wright, S. (1934). The method of path coefficients. Annals of Mathematical Statistics, 5, 161–215. Wold, H. A. (1954). Causality and econometrics. Econometrica, 22(2), 162–177. Yves, R. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. 15 Chapter 2 DATA ENTRY AND EDIT ISSUES CHAPTER CONCEPTS Data set formats Data editing issues Measurement scale Restriction of range Missing data Outliers Linearity Non-normality Sample size and degrees of freedom Start values Non-positive definite matrices Heywood case (negative variance) DATA SET FORMATS An important first step in using an SEM software program is to be able to enter raw data and/or import data.
A Beginner’s Guide to Structural Equation Modeling by Randall E. Schumacker, Richard G. Lomax