Before learning how to interpret a factor analysis, it's important for a person to first understand the basics of factor analysis. What is factor analysis all about? The process of reducing many variables to smaller numbers, is known as factor analysis. The result analysed are kept in fewer numbers of factors. So if they are many variables with common data, they can all be interpreted in a common ratio or score. Instead of using a large variable, an organization can simply use the common score for future data analysis, which will be easier and save time. There are different methods of analyzing factors, which are the principal component, common factor, image factoring, maximum likelihood analysis, and other methods. However, the principal component analysis method has proven to be the best method for factorization, and this method is mainly used by most organizations.
Principal component, which can also be called PCA, is popular among researchers. They use it to extract large variance, that is later deposited into the first factor. When it's true with extracting and depositing into factor-1, then it uses the same process to extract more variance for a second factor, after removing the old variance. The process of extracting and depositing goes on until an organization is satisfied with the factors obtained, that's why PTA, or principal component is widely used.
A common factorization can be used instead of, or in replacement for principal components, as it is the most-common method, after PCA. This type of factorization is easier to use, it simply extracts those variables that have similar data, and puts them into factors, it is mainly used in SEM, etc. Others are image factoring, which works perfectly, as it is based-on correlation matrix, but uses OLS regression for factorization. While maximum likelihood uses likelihood method for factorization, even if it uses correlation matrix also.
How do you interpret these factors that are analysed? The first step is to determine the numbers of factors present, this can be done by extraction. If a person doesn't know the right number of factors to use, then they might be problems later on. All the methods listed above are ways of determining numbers of factors, so a person can choose any type that suits his desire. After an individual has done step one, then the next step is to interpret. Interpretation can only be done when you have determined the number of factors. It's advisable to use maximum likelihood for a duplicate of your analysis, then examine the pattern at which each variable is being extracted, this will show the ones that have more influence on others.
Finally, when you are done with both steps, the last thing to do, is to check your data for problems. Always check your data to avoid making mistakes. When using advanced computers, you can check for errors easily, by using some special function keys. You can review your work with the computer that you're using, this will highlight words with error in spellings, punctuation, and others.