By Larry Hatcher, Norm O'Rourke
This easy-to-understand advisor makes SEM available to all clients. This moment version includes new fabric on sample-size estimation for course research and structural equation modeling. in one elementary quantity, scholars and researchers will locate the entire info they wish so one can grasp SAS fundamentals ahead of relocating directly to issue research, direction research, and different complex statistical methods.
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Extra info for A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling (2nd Edition)
ALL RIGHTS RESERVED. com/bookstore. Chapter 1: Principal Component Analysis 31 Step 7: Preparing a Formal Description of the Results for a Paper The preceding analysis could be summarized in the following way: Principal component analysis was performed on responses to the 6-item questionnaire using ones as prior communality estimates. The principal axis method was used to extract the components, and this was followed by a varimax (orthogonal) rotation. 00; results of a scree test also suggested that only the first two were meaningful.
Went out of my way to do a favor for a coworker. Went out of my way to do a favor for a relative. Went out of my way to do a favor for a friend. Gave money to a religious charity. Gave money to a charity not affiliated with a religion. Gave money to a panhandler. Questions 4, 5, and 6 all seem to deal with giving money to persons in need. It is therefore reasonable to label component 1 the “financial giving” component. 8. Repeat this process to name the remaining retained components. In the present case, there is only one remaining component to name: component 2.
Such a component therefore accounts for a meaningful amount of variance and (in theory) is worthy of retention. 00 accounts for less variance than contributed by one variable. The purpose of principal component analysis is to reduce a number of observed variables into a relatively smaller number of components. This cannot be effectively achieved if you retain components that account for less variance than had been contributed by individual variables. 00 are viewed as trivial and are not retained.
A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling (2nd Edition) by Larry Hatcher, Norm O'Rourke