By Larry Hatcher, Norm O'Rourke

ISBN-10: 1612903878

ISBN-13: 9781612903873

This easy-to-understand advisor makes SEM obtainable to all clients. This moment version includes new fabric on sample-size estimation for course research and structural equation modeling. in one simple quantity, scholars and researchers will locate the entire details they want with the intention to grasp SAS fundamentals earlier than relocating directly to issue research, course research, and different complicated statistical strategies.

**Read Online or Download A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling (2nd Edition) PDF**

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**Additional resources for A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling (2nd Edition)**

**Example text**

71 indicates that approximately 71% of the total variance is accounted for by components 1 and 2. 84, indicating that 84% of the variance is accounted for by components 1, 2, and 3. If you were to use 70% as the “critical value” for determining the number of components to retain, you would retain only components 1 and 2 in the present analysis. The primary advantage of the proportion of variance criterion is that it leads you to retain a group of components that combined account for a relatively large proportion of variance in the dataset.

The eigenvalue-one criterion has a number of positive features that contribute to its utility. Perhaps the most important reason for its use is its simplicity. 00. Yet this criterion often results in retaining the correct number of components, particularly when a small to moderate number of variables are analyzed and the variable communalities are high. 59. There are, however, various problems associated with the eigenvalue-one criterion. , when many variables are analyzed, when communalities are small).

Cary, North Carolina, USA. ALL RIGHTS RESERVED. com/bookstore. Chapter 1: Principal Component Analysis 15 Factor Pattern Factor1 Factor2 V1 58 * 70 * V2 48 * 53 * V3 60 * 62 * V4 64 * -64 * V5 68 * -45 * V6 68 * -46 * Printed values are multiplied by 100 and rounded to the nearest integer. 4 are flagged by an '*'. 76914 Rotated Factor Pattern Factor1 Factor2 V1 0 91 * V2 3 71 * V3 7 86 * V4 90 * -9 V5 81 * 9 V6 82 * 8 Printed values are multiplied by 100 and rounded to the nearest integer. 4 are flagged by an '*'.

### A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling (2nd Edition) by Larry Hatcher, Norm O'Rourke

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