By Randall E. Schumacker, Richard G. Lomax
Noted for its crystal transparent reasons, this booklet is taken into account the main finished introductory textual content to structural equation modeling (SEM). famous for its thorough assessment of uncomplicated strategies and a wide selection of versions, this e-book larger prepares readers to use SEM to various study questions. Programming info and using algebra are saved to a minimal to assist readers simply clutch the strategies to allow them to behavior their very own research and critique similar examine. that includes a better emphasis on statistical energy and version validation than different texts, every one bankruptcy positive factors key strategies, examples from a number of disciplines, tables and figures, a precis, and workouts.
Highlights of the widely revised 4th variation include:
-Uses varied SEM software program (not simply Lisrel) together with Amos, EQS, LISREL, Mplus, and R to illustrate applications.
-Detailed advent to the statistical tools on the topic of SEM together with correlation, regression, and issue research to maximise figuring out (Chs. 1 – 6).
-The five step method of modeling information (specification, identity, estimation, trying out, and amendment) is now lined in additional aspect and ahead of the modeling chapters to supply a extra coherent view of ways to create versions and interpret effects (ch. 7).
-More dialogue of speculation trying out, strength, sampling, influence sizes, and version healthy, serious subject matters for starting modelers (ch. 7).
- every one version bankruptcy now specializes in one strategy to improve realizing via supplying extra description, assumptions, and interpretation of effects, and an workout regarding 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 applications (Ch. 1).
-Guidelines for reporting SEM learn (Ch. 16).
-www.routledge.com/9781138811935 which gives entry to info units that may be used with any software, hyperlinks to different SEM examples, comparable readings, and magazine articles, and extra.
Reorganized, the hot version starts with a extra particular advent to SEM together with a number of the software program applications to be had, via chapters on information access and enhancing, and correlation that is serious to realizing how lacking information, non-normality, dimension, and restrict of diversity in ratings impacts SEM research. a number of regression, course, and issue types are then reviewed and exploratory and confirmatory issue research is brought. those chapters show how saw variables percentage variance in defining a latent variables and introduce how size mistakes should be faraway from saw variables. bankruptcy 7 info the five SEM modeling steps together with version specification, id, estimation, trying out, and amendment besides a dialogue of speculation checking out and the similar problems with energy, and pattern and influence sizes.Chapters eight to fifteen offer finished introductions to various SEM types together with a number of crew, Second-Order CFA, Dynamic issue, Multiple-Indicator Multiple-Cause, combined Variable and combination, Multi-Level, Latent development, and SEM interplay versions. all of the five SEM modeling steps is defined for every version besides an software. bankruptcy routines offer perform with and improve knowing of the research of every version. The publication concludes with a overview of SEM directions for reporting learn.
Designed for introductory graduate classes in structural equation modeling, issue research, complicated, multivariate, or utilized records, quantitative innovations, or facts II taught in psychology, schooling, enterprise, and the social and healthcare sciences, this functional publication additionally appeals to researchers in those disciplines. must haves comprise an advent to intermediate statistics that covers correlation and regression principles.
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Additional info for A Beginner’s Guide to Structural Equation Modeling
Schafer, J. L. (1997). Analysis of incomplete data. Boca Raton, FL: Chapman & Hall/CRC Press. Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103, 677–680. 29 Chapter 3 CORRELATION CHAPTER CONCEPTS Types of correlation coefficients Factors affecting correlation Outliers Correction for attenuation Non-positive definite matrices Bivariate, part, and partial correlation What is a suppressor variable? Correlation versus causation In the previous chapter, we explained several data preparation issues that can affect structural equation modeling.
Statistical packages that provide SEM software permit the researcher to conduct much needed data screening and editing (SPSS—AMOS, SAS—Proc Calis, Statistica—SEPATH, STATA—SEM). Nothing prevents a researcher from using a statistical package to edit data prior to using it in a stand-alone SEM software program (EQS, Mplus, Mx, R). A researcher should also be aware of important data editing features needed prior to SEM analysis, whether available in a statistics package or the SEM software. This involves checking for missing data, conducting homogeneity of variance tests, normality tests, and data output options.
Need to consider range of values obtained for variables, as restricted range of one or more variables can reduce the magnitude of correlations. Need to consider missing data on one or more subjects for one or more variables as this can affect SEM results. Cases are lost with listwise deletion, pairwise deletion is often problematic (for example, different sample sizes), and thus modern imputation methods are recommended. Need to consider outliers as they can affect statistics such as means, standard deviations, and correlations.
A Beginner’s Guide to Structural Equation Modeling by Randall E. Schumacker, Richard G. Lomax