1. Would you exclude any items on the questionnaire on the basis of multicollinearity
or singularity?
A: In the correlation Matrix output table, there is no any R value variables great
than .9. Therefore, there is no any multicollinearity or singularity occurred. There is
no need to exclude any items in the questionnaire.
2. Is the sample size adequate? Explain your answer quoting any relevant statistics.
A: According to Field (2005), 300 cases is probably adequate and communalities after
extraction should be above 0.5. As for TOSSE dataset, the total sample size is 239
cases which is still acceptable when communalities after extraction should be set to .6.
3. How many factors should be retained? Explain your answer quoting any relevant
statistics?
A: Because SPSS extract all factors with eigenvalues greater than 1 in "Total Variance
Explained" table, the total remaining factors are five
4. What method of rotation have you used and why?
A: I used Obliqure rotation because the researcher of TOSSE believed that factors
were related. Orthogonal rotation is used when factors are theoretically independent.
5. Which items load onto which factors? Do these factors make psychological sense
(i.e. can you name them based on the items hat load onto them?)
A: Looking at the "Rotated component matrix" table, I can tell factor 1 represents an
enthusiasm for experimental design, factor 2 represents a profound love of statistics,
factor 3 represents a love of teaching, factor 4 and 5 seems like the factor of a
complete absence of normal interpersonal skill. However, some of items in this table
are overlap with other factors so I think there are some problems in this questionnare.