Thank you. I'll do my best, once again...
I spent hours preparing a data file (a Data view) and a sample file, a variable view, the ideal output in its desired form. But I'm faced with an error "Sorry, the board attachment quota has been reached." I can't upload anything, not even a small gif.
Data view: http://www.bayimg.com/gapffAafE
In the sample data view below, you will notice that all variables are nominal.
V01 to V10 are dichotomous (with 0-1 values, where 0 is a negative evaluation, and 1 is a positive one). Depending on the measure,
these variables could be negative/positive perceptions, satisfaction, beliefs, etc.
The other two variables are 'Gender' (1-2) and 'AgeCat' (age category) (1-4).
Variable view: http://www.bayimg.com/GApfjAaFE
The 4 first variables (V01 to V04) are used to calculate an overall score pertaining to 'Sound quality' (call it an index, a ratio, a scale, a combined measure or a global score, etc.). Let's call it an Index for now: Index 1 = Sound Quality
. An index number is a number (as a ratio) derived from a series of observations and used as an indicator or measure (The Merriam Webster Dictionary).
Index 2 ( 'Choice of bands') will be derived from the 6 following variables (V05 to V10).
Ideal output: http://bayimg.com/HApFaAaFe
Two (2) things are highly desirable here:
1- To be able to compute the overall index number for any giving index (for the whole sample, excluding missing values).
2- To be able to compare sub-samples (on the base of indices) as in the image above, and of course to find a way to know if the diffrences between sub-samples are statistically significant.
So, the Index overall score =
Overall % positive evaluations = Total Sum of positive evaluations / Total number of evaluations
For example, for males: 149 / 165 = 90,3%
This overal score could also be obtained by a weighted mean(weighted mean of all values of column '% positive evaluations'), not by an arithmetic one:
For example, for male respondents:
= [ (86% x 42) + (90% x 41) + etc.] / 165 = 90,3 %
Finally, here is the way I used to present the results when sample sizes where smaller. The only thing missing in this presentation is statistical significance.
(FYI: I used to use ViewSav, a a free utility viewer for SPSS data files and a real-time codebook).
Thank you for your patience.