Describe the data. State where the data originated from and how it was collected. If there are any preliminary data analyses or data exploration procedures you wish to perform, do them and state their results before performing the factor analysis.
State the objective of your factor analysis study. You should clarify what you hope the end result will be, what your hypothesis is and why you have chosen to perform factor analysis over other forms of data analysis.
Describe the method you used to select the number of factors in your analysis. For example, if you used a scree plot, attach the plot and state where you feel the "elbow" (drop-off point) of the plot is. State your criterion for selecting the number of factors for the upcoming factor analysis.
Present the result of the common factor model solution. Present the solution as a table, with the variables as rows and the factors as columns.
Analyze the common factor model solution. Describe the variance as explained by each factor in the solution and list the final communality estimates.
Give the final rotation method used. It is also appropriate to state all rotation methods you attempted before choosing a final rotation method. State why the final rotation method satisfied your hypothesis.
Present your final solution. Do this in the same manner that you presented the common factor model solution.
Analyze the final solution. Describe the variance explained by the final factors and list the final communality estimates for this solution. This is also a good time to compare the final solution to the common factor model solution and state why this solution is an improvement.