1

I have done a study on whether personality and demographics predict interaction on Facebook brand pages. I have used a Big five personality scale and the demographics include, sex, age, marital status, employment status and education level. Interaction on Facebook brand pages was measured using 6 different questions:

  1. How many total brand pages have you liked? 0-5, 6-11, 12-20, 21-30, over 30
  2. How much time per hour do you spend using Facebook brand pages? under 1 hour, 1-2 hours, 2-4 hours, 4-6 hours, 6+ hours
  3. How many times per week do you comment on a brand pages post? (answers from 0 to 6+)
  4. How many times per week do you share a brand pages post (answers from 0 to 6+)
  5. How many times per week do you like a brand pages post (answers from 0 to 6+)
  6. How many times per week do you post on a brand pages wall (answers from 0 to 6+)

So far I have done a Pearson's correlation so I can see where the positive and negative correlations are.

Which statistical test would be best to use? I am using SPSS. I was thinking about doing a multiple regression but the only way I could do it is by doing 6 different ones for each D.V. I can't do a factor analysis because the data is not interval.

gung - Reinstate Monica
  • 132,789
  • 81
  • 357
  • 650
arnika
  • 11
  • 1
  • 3
    Re question 2: I would like to meet the multitasker who manages to spend 6+ hours *per hour* using Facebook brand pages! – whuber Nov 21 '14 at 17:37
  • It may well be possible to use FA w/ likert items, see: [Factor analysis of questionnaires composed of likert items](http://stats.stackexchange.com/q/2374/7290). – gung - Reinstate Monica Nov 21 '14 at 17:49
  • What's wrong with 6 multiple regressions? If you have 6 outcomes ... – Jeremy Miles Nov 21 '14 at 18:31
  • I wasn't sure if it was the right thing to do! Does running multiple regressions on the same data set increase family wise error? – arnika Nov 21 '14 at 19:30
  • Yes, but it's commonly done. You could do a multivariate regression but if your outcomes are correlated you have less power. – Jeremy Miles Nov 21 '14 at 23:33

0 Answers0