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I randomized my survey, and now I have my data on SPSS (and all cleaned up) but when trying to run my Cronbach's $\alpha$ I have a problem.

Because I have two treatments (sexualised and normal) all my measures are present twice in my data set. For example, “similarity” has 3 items but now I have 6 variables: 3 for the sexualized and 3 for the normal condition.

Sim1  
Sim2  
Sim3  
aSim1  
aSim2  
aSim3  

SPSS will not allow me to combine 2 treatments because I have no data that has answers for the 6 (obviously).

Do I calculate them separately and then get the average between the two, or do I report both Cronbach's $\alpha$s for the 2 treatments?

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  • $\begingroup$ What do you want to do with $\alpha$ and how do you plan to use these data afterwards? $\endgroup$
    – Gala
    Jul 18, 2013 at 20:39
  • $\begingroup$ Also what's your sample size? $\endgroup$
    – Gala
    Jul 18, 2013 at 20:59
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    $\begingroup$ Can you present examples of items? The likely answer is that you calculate the alpha separately. $\endgroup$
    – Behacad
    Jul 18, 2013 at 21:09
  • $\begingroup$ @Behacad +1 to your comment. In fact you definitely cannot meaningfully do anything else that calculating alpha separately on each sub-sample in my opinion but the likely answer is that you shouldn't be calculating alpha at all. $\endgroup$
    – Gala
    Jul 18, 2013 at 21:16
  • $\begingroup$ Ok for example I am using purchase intention (DV) made up of 3 measures: one being perceived social norm. To make sure I am using valid and reliable measures I need to group all my items of social norm to get the cronbachs. but Because I have 2 treatments, sexualized and normal it doesn't allow me to combine the items for social norm. I have 3 items for social norm but because of the 2 treatmens it has multiplied my social norm items by 2. Thus to present a cronbachs alpha should I do them separately and then get the average? or report the 2 separately? thanks!! $\endgroup$
    – Carmen PM
    Jul 18, 2013 at 21:54

1 Answer 1

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Given what you have stated, you should calculate the alpha's separately. For example, you could state that the measure of social X had an alpha value of .75 in sample 1 and of .80 in sample 2. If there are very few items (e.g., around 3), average inter-item correlation may also be used instead of Cronbach's alpha.

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    $\begingroup$ It is always possible to interpret alpha in terms of a quasi-average correlation, and vice-versa. alpha/(1-alpha) = kr/(1-r), where k = the number of items and r = (average covariance)/(average variance). From this we get alpha = kr/(k*r + 1-r) and r = alpha/(alpha + k(1-alpha)). $\endgroup$ Jul 19, 2013 at 7:42
  • $\begingroup$ Thank you everyone. Ray you have kind of lost me! possibly simplest thing to do is Behacad's first solution. $\endgroup$
    – Carmen PM
    Jul 19, 2013 at 9:37

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