Although spss anxiety explain some of this variance, there may be systematic factors. Figure 5 the first decision you will want to make is whether to perform a principal components analysis or a principal factors analysis. Feb 03, 2012 how to carry out a simple factor analysis using spss. Factor analysis is based on the correlation matrix of the variables involved, and correlations usually need a large sample size before they stabilize. Nov 11, 2016 30 factor analysis factor the initial number of factors is the same as the number of variables used in the factor analysis. Similar to factor analysis, but conceptually quite different. Factor analysis has no ivs and dvs, so everything you want to get factors for just goes into the list labeled variables. Factor analysis is often used in data reduction to identify a small number of factors that explain most of the variance that is observed in a much larger number of manifest variables. In this video, we look at how to run an exploratory factor analysis principal components analysis in spss part 2 of 6. How to perform a principal components analysis pca in spss. Factor analysis and principal component analysis pca c. Using factor analysis for data reduction an industry analyst would like to predict automobile sales from a set of predictors. As for the factor means and variances, the assumption is that thefactors are standardized. Run this stepbystep example on a downloadable data file.
Factor analysis in spss to conduct a factor analysis. You can do this by clicking on the extraction button in the main window for factor analysis see figure 3. Also in these cases, instead of 14 factors spss proposes way less 4, 6. Aug 19, 2014 this video describes how to perform a factor analysis using spss and interpret the results. The theory of factor analysis was described in your lecture, or read field 2005 chapter 15. Within this dialogue box select the following check boxes univariate descriptives, coefficients, determinant, kmo and bartletts test of sphericity, and reproduced. Factor analysis is based on the correlation matrix of the variables involved, and correlations.
Spss will not only compute the scoring coefficients for you, it will also output the factor scores of your subjects into your spss data set so that you can input them into other procedures. In the descriptives window, you should select kmo and bartletts test of sphericity. Aug 27, 2017 exploratory factor analysis in spss example 01 duration. Factor analysis using spss ml model fitting direct quartimin, promax, and varimax rotations of 2 factor solution. As in spss you can either provide raw data or a matrix of correlations as input to the cpa factor analysis. They are often used as predictors in regression analysis or drivers in cluster analysis. In this example, only the first three factors will be retained as we requested. Factor analysis in spss to conduct a factor analysis reduce. Factor analysis is a statistical method that is used to investigate whether there are underlying latent variables, or factors, that can explain the patterned correlations within a set of observed. To run a factor analysis, use the same steps as running a pca analyze dimension reduction factor except under method choose principal axis factoring. Sep 26, 2016 this feature is not available right now. Results including communalities, kmo and bartletts test, total.
The key concept of factor analysis is that multiple observed variables have similar patterns of responses because of their association with an underlying latent variable, the factor, which cannot easily be measured. Conduct and interpret a factor analysis statistics solutions. In the factor analysis window, click scores and select save as variables, regression, display factor score coefficient matrix. In this portion of the seminar, we will continue with the example of the saq. For example, it is possible that variations in six observed variables mainly reflect the variations in two unobserved underlying variables. The broad purpose of factor analysis is to summarize. Confirmatory factor analysis borrows many of the same concepts from exploratory factor analysis except that instead of letting the data tell us the factor structure, we predetermine the factor structure and perform a hypothesis test to see if this is true.
In more advanced models of factor analysis, the condition that the factors are independent of one another can be relaxed. This video demonstrates how interpret the spss output for a factor analysis. Interpreting spss output for factor analysis youtube. Factor analysis example free download as powerpoint presentation. This video describes how to perform a factor analysis using spss and interpret the results. For example, a confirmatory factor analysis could be performed if a researcher wanted to. Skewness is another problem in the tas that i see in this example and. Spss factor can add factor scores to your data but this is often a bad idea for 2 reasons. Note that we continue to set maximum iterations for convergence at 100 and we will see why later. A human resources manager wants to identify the underlying factors that explain the 12 variables that the human resources department measures for each applicant. Principal components analysis pca, for short is a variablereduction technique that shares many similarities to exploratory factor analysis.
I demonstrate how to perform and interpret a factor analysis in spss. Factor analysis is a technique that requires a large sample size. Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, a confirmatory factor analysis could be performed if a researcher wanted to validate the factor structure of the big five personality traits using the big five inventory. For example, people may respond similarly to questions about income, education, and occupation, which are all associated with the latent variable socioeconomic status. Introduction to factor analysis and factor analysis vs. Click on the descriptives button and its dialogue box will load on the screen.
When conducting a factor analysis for some of my groups the method is not working. Mar 26, 2015 exploratory factor analysis in spss example 01. Looking at the communalities table, all extraction values of all items equal 1, which to my knowledge is not as it should be. Factor analysis using spss 2005 discovering statistics. Use principal components analysis pca to help decide. Dasl is a good place to find extra datasets that you can use to practice your analysis techniques. In thecontext of the present example, this means in part that thereis norelationship between quantitative and verbal ability. In the first part of this example, an exploratory factor analysis with. Running a common factor analysis with 2 factors in spss. Expert sessions delivered on factor analysis and structure equation modeling using spss and amos in national level two week faculty development programme on advanced data analysis for business. Its pretty common to add the actual factor scores to your data. Its aim is to reduce a larger set of variables into a smaller set of artificial variables, called principal components, which account for most of the variance in the original variables. Principal components is the default extraction method in spss.
This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output. Spss will extract factors from your factor analysis. This form of factor analysis is most often used in the context of structural equation modeling and is referred to as confirmatory factor analysis. Epq see item analysis and factor analysis with spss escalate see threeway nonhierarchical loglinear analysis. Factor analysis in spss to conduct a factor analysis, start from the analyze menu. If you are already comfortable working with statistical software packages like r, sas, spss, or stata, just export your survey data from analyze to download the data into the format that fits your software. Tabachnick and fidell 2001, page 588 cite comrey and lees 1992 advise regarding sample size. Factor analysis example visual cortex statistical analysis. Factor scores will only be added for cases without missing values on any of the input variables. Principal components pca and exploratory factor analysis. Human resources employees rate each job applicant on various characteristics using a 1 low through 10 high scale.
Take the example of item 7 computers are useful only for playing games. Factor analysis researchers use factor analysis for two main purposes. Factor analysis can also be used to generate hypotheses regarding causal mechanisms or to screen variables for subsequent analysis for example, to identify collinearity prior to performing a linear regression analysis. But factor analysis is a more advanced analysis technique. With respect to correlation matrix if any pair of variables has a value less than 0. This procedure is intended to reduce the complexity in a set of data, so we choose data reduction. How to carry out a simple factor analysis using spss. However, many of the predictors are correlated, and the analyst fears that this might adversely affect her results. Some are my data, a few might be fictional, and some come from dasl.