This tutorial provides practical experience conducting exploratory factor analyses with several different data sets.
It is recommended that you save your syntax and output for each analysis and ask questions about anything you don't understand.
For each analysis:
What is the factor structure of the Resilience Scale? The designers of the 25-item Resilience Scale (Wagnild & Young. 1993) purported five factors. A subset of 15 of the original items is provided from data collected from young Australian adults by Neill & Dias (2001). Check whether a five factor solution holds up for the data. For this factor analysis, we are interested in developing a theoretical understanding of the underlying psychological components of resilience, so use Principal Axis Factoring (PAF), which looks at the shared variance amongst the items, not all the items' variance.
You should find that there are really not enough primary loadings on 4 or 5 factors to justify their presence, therefore try 2 and 3 factors. Best approach is probably 2 factors ("taking control" and "taking it easy"), with 3 to 5 items removed (at least remove the three worst items 2, 8, and 17) and using an oblimin rotation.
It seems that according to this data, psychological resilience consists of two main underlying components. The first factor, "Solve" is about taking control, making plans, being determined, task oriented, active, and disciplined, and solving problems (7 items - 1, 14, 10, 15, 6, 24, 21). The second factor, "Flow" is about a flexible approach to coping, including being able to take things in one's stride, taking it easy, laughing things off, and finding alternative ways through problems (5 items - 19, 7, 23, 16, 9). People who exhibit both these qualities are people who are most likely to "psychologically resilient" to negative consequences of experiencing risk factors.
The designer of the Self Description Questionnaire - II, a self-concept questionnaire, for adolescents (SDQ-II), Prof. Herb Marsh, proposes 11 factors. This is a sample of data pertaining to 7 of those factors, collected from Australian adolescents. Check to see whether there are 7 factors. Use Principle Components (assume we are doing this in order to calculate factor scores for each self-concept factor).
Check the scree plot - it will suggest looking at 3, 5 and 8 factors. Yet, further exploration of the factor loadings suggests that 6 or 7 factors make more sense. However, there are some cross-loadings between the Opposite-Sex Relations and Physical Appearance items. These can be minimised by using an oblimin rotation. A 7 factor solution makes most sense. Note that if 6 factors are used, that it seems that Opposite-Sex Relations join in one factor with Physical Appearance. Whilst understandably related, it would make more sense to keep Physical Appearance and Opposite Sex Relations as a separate factors.
It is also important to test for structural invariance across cohorts within the sample. Further checking of the SDQ data 6 and 7 factor solutions should take place across Gender. If the factor analyses are done separately by Gender, it becomes apparent that the 6 factor solution can apply to both genders, whereas the 7 factor solution seems to only apply to one gender. Thus, this is an issue which require further thinking and investigation before ultimately deciding on the most appropriate factor structure.
This file contains data for all 24 items in the Life Effectiveness Questionnaire version H. How many factors are evident in this data set?
It is important to test for structural invariance across cohorts within the sample. Using the LEQ data, conduct your factor analysis separately for males and females. Is life effectiveness structured similarly for males and females?
Does the LEQ factor structure also hold up across participant age?
Internal consistency (or internal reliability) is often measured using Cronbach's alpha.
Also see Q4 (resilience.sav) which involves calculating the internal consistency and composite scores for two psychological resilience factors.
collected approximately 1 month apart (Time 0 and Time 1).