By Randall E. Schumacker, Richard G. Lomax
This best-seller introduces readers to structural equation modeling (SEM) to allow them to behavior their very own research and critique similar learn. famous for its available, utilized method, chapters disguise simple innovations and practices and desktop input/output from the loose scholar model of Lisrel 8.8 within the examples. every one bankruptcy positive aspects an summary, key options, a precis, a variety of examples from numerous disciplines, tables, and figures, together with direction diagrams, to aid with conceptual understanding.
The booklet first studies the fundamentals of SEM, information entry/editing, and correlation. subsequent the authors spotlight the fundamental steps of SEM: version specification, id, estimation, checking out, and amendment, by means of matters on the topic of version healthy and tool and pattern dimension. Chapters 6 via 10 stick to the stairs of modeling utilizing regression, direction, confirmatory issue, and structural equation types. subsequent readers discover a bankruptcy on reporting SEM examine together with a list to steer decision-making, via one on version validation. Chapters thirteen via sixteen offer examples of assorted SEM version purposes. The ebook concludes with the matrix method of SEM utilizing examples from prior chapters.
Highlights of the recent variation include:
* an internet site with uncooked information units for the book's examples and workouts to allow them to be used with any SEM application, all the book's workouts, hotlinks to comparable web pages, and solutions to all the routines for Instructor’s only
* New troubleshooting how to handle the main usually encountered problems
* Examples now reference the loose scholar model of Lisrel 8.8
* multiplied assurance of complicated versions with extra on multiple-group, multi-level, & blend modeling (Chs. thirteen & 15), second-order and dynamic issue types (Ch. 14), and Monte Carlo tools (Ch. 16)
* elevated assurance of pattern dimension and gear (Ch. five) and reporting study (Ch. 11)
* New magazine article references support readers larger comprehend released learn (Chs. thirteen – 17) and 25 % new workouts with solutions to part within the publication for scholar review.
Designed for introductory graduate point classes in structural equation modeling or issue research taught in psychology, schooling, enterprise, and the social and healthcare sciences, this useful e-book additionally appeals to researchers in those disciplines. An knowing of correlation is believed. To entry the web site stopover at the ebook web page or the Textbook source web page at http://www.psypress.com/textbook-resources/ for extra information.
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Additional resources for A beginner's guide to structural equation modeling
The Import Data option permits inputting raw data files or SPSS saved files. dat, is in the PRELIS folder (PR2EX). When selecting this file, you will need to know the number of variables in the file. sav, is in the SPSS folder (SPSSEX). Once you open this file, a PRELIS system file is created. indb 16 3/22/10 3:25:13 PM Data Entry and Data Editing Issues 17 Once the PRELIS system file becomes active, then it needs to be saved for future use. 00 will appear. ). psf) activates a pull-down menu that permits data editing features, data transformations, statistical analysis of data, graphical display of data, multilevel modeling, and many other related features.
Need to consider outliers as they can affect statistics such as means, standard deviations, and correlations. They can either be explained, deleted, or accommodated (using either robust statistics or obtaining additional data to fill-in). Can be detected by methods such as box plots, scatterplots, histograms or frequency distributions. Need to consider whether variables are linearly related, as nonlinearity can reduce the magnitude of correlations. Can be detected by scatterplots. Can be dealt with by transformations or deleting outliers.
PRELIS can deal with missing data. indb 30 3/22/10 3:25:21 PM Data Entry and Data Editing Issues 31 c. LISREL can compute descriptive statistics. d. PRELIS can compute descriptive statistics. 4. Explain how each of the following affects statistics: a. Restriction of range b. Missing data c. Outliers d. Nonlinearity e. Nonnormality References Anderson, N. H. (1961). Scales and statistics: Parametric and non-parametric. Psychological Bulletin, 58, 305–316. , & Savla, J. (2009). Statistical power analysis with missing data: A structural equation modeling approach.
A beginner's guide to structural equation modeling by Randall E. Schumacker, Richard G. Lomax