Computer programs are available to implement both of the approaches: principal components analysis and common factor analysis. We discuss the use of SPSS and SAS in detail in the subsequent sections. Here, we briefly describe the use of MINITAB. In MINITAB, factor analysis can be assessed using Multivariate-Factor analysis. Principal components or maximum likelihood can be used to determine the initial factor extraction. If maximum likelihood is used, specify the number of factors to extract. If a number is not specified with a principal component extraction, the program win set it equal to a number of variables in the data set. Factor analysis is not available in EXCEL.
SPSS and SAS Computerized Demonstration Movies
We have developed computerized demonstration movies that give step-by-step instructions for running all the SPSS and SAS Learning Edition programs that are discussed in this chapter. These demonstrations can be downloaded from the Web site for this book. The instructions for running these demonstrations are given in Exhibit 14.2.
SPSS and SASScreen Captures with Notes
The step-by-step instructions for running the various SPSS and SAS Learning Edition programs discussed in this chapter are also illustrated in screen captures with appropriate notes. These screen captures can be downloaded from the Web site for this book.
To select this procedure using SPSS for Windows, click:
Analyze>Data Reduction>Factor …
The following are the detailed steps for running principal components analysis on the toothpaste attribute ratings (V1 to V6) using the data of Table 19.1
- Select ANALYZE from the SPSS menu bar.
- Click DIMENSION REDUCTION and then FACTOR.
- Move “Prevents Cavities [v1],” “Shiny Teeth [v2],” “Strengthen Gums [v3],” “Freshens Breath [v4],” “Tooth Decay Unimportant [v5],” and “Attractive Teeth [v6].” into the VARIABLES box.
- 4. Click on DESCRIPTIVES. In the pop-up window, in the STATISTICS box check INITIAL SOLUTION. In the CORRELATION MATRIX box check KMO AND BARTLETT’S TEST OF SPHERICITY and also check REPRODUCED. Click CONTINUE.
- Click on EXTRACTION. In the pop-up window, for METHOD select PRINCIPAL COMPONENTS (default). In the ANALYZE box, check CORRELATION MATRlX .
In the EXTRACT box, select BASED ON EIGENVALUE and enter I for EIGENVALUES GREATER THAN box. In the DISPLAY box check UNROTATED FACTOR SOLUTION. Click CONTINUE.
- Click on ROTATION. In the METHOD box check VARIMAX. In the DISPLAY box check ROTATED SOLUTION. Click CONTINUE.
- Click on SCORES. In the pop-up window, check DISPLAY FACTOR SCORE COEFFI· CLIENT MATRIX. Click CONTINUE.
- Click OK.
The procedure for running common factor analysis is similar, except that in step 5, for METHOD select PRINCIPAL AXIS FACTORING.