I am working on an analysis using exploratory factor analysis (EFA) with the common factor model. This question concerns a methodological issue. Any insights from someone who knows about EFA would be appreciated.
We measured the wellbeing of people using a 15 question survey. The same questionnaire was given the same 100 subjects at 3 different times (there were large gaps in time between when the surveys were administered, therefore we are assuming there was no time dependence [such as carry-over effect]). The goal is to use factor analysis to determine a fixed set of common factors and then calculate the factor scores and to compare the scores of subjects between time points.
Below is my strategy for the analysis. Does this sound reasonable?
Analysis Strategy: Combine all the data as it if were from a single location. That is to say, create a data set with 100 observations from time 1 and append the 100 observations from time point 2. Then append the 100 observations from time point 3. This would give a combined data set with a total of 300 observations.
Using the above data, fit an EFA model using all 15 variables and 300 observations and obtain factors. After computing the factor scores, again treat the data as if it were from 3 different time points (i.e. 100 subjects measured at three time points). Analyze the factors scores with i.e. ANOVA to test if factor scores of a factor change between the time points.