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Incidentally, Cronbach's $\alpha$ is often misinterpreted and has been thoroughly criticized. Even the very idea of aiming for higher internal consistency has been called into question (most notably by Cattell, cf. “bloated specifics”).
21 1 2. whether Cronbach's alpha can be calculated for all types of questions even if they are not on scale format No. Classic alpha - only for scale (metrical) data. Or binary (then it is called Kuder-Richardson). – ttnphns. Feb 1, 2017 at 7:27.
Cronbach's alpha continuous and dichotomous data in SPSS. I have one question about using SPSS to calculate Cronbach's alpha of a measure that draws on two types of items: one yields ordinal data and the other dichotomous. The ordinal data are produced through 4-point rating items and the dichotomous data through true-and-false questions.
I found in the wiki article a definition of a standardized Cronbach's alpha but nothing is said what it is and about its relation to the original Cronbach's alpha: I found at What is Cronbach's Alpha intuitively? a well explained interpretation of Cronbachs alpha. Does the standardized Cronbach's alpha have the same interpretation? Or is it ...
My personal observation has been that when someone calculates Alpha for a mixture of scales like Dichotomous, polychotomous, likert etc, then probability of alpha being negative or low is higher. So the conclusion, from my observation, may be personal or biased, is that the use consistent scales be used when calculating Cronbach's Alpha. Share.
Information on Cronbach's alpha is here and any standard statistics package will calculate this for you. You will need to use the individual trial data to do the calculation so K=200 . Assuming you're going to be using R or similar, you'll need the data in wide format.
Cronbach's alpha coefficient is functionally equivalent to the third formulation listed above: the average measures consistency formulation or ICC(C,k). If you don't believe me, ask SPSS to output the two-way consistency ICCs and compare the alpha value it gives you to the average measures ICC it gives you; they will be the same.
Cronbach's $\alpha$ is a measure of internal consistency of a questionnaire or test. It says how correlated the items are that are included in the scale. This is the reason why you need preferably much more than two items: you cannot correlate one item with itself and if you had only two items you could use a "traditional" correlation between ...
The mean correlation among all 110 items is m [r] = .085. If one erroneously applies the alpha reliability formula to these 110 items, the result would be: alpha = 110∗.085 1+(110−1)∗.085 =.91 a l p h a = 110 ∗.085 1 + (110 − 1) ∗.085 =.91. Note that Cronbach’s alpha is the same, within rounding error, in both situations, yet the ...
edited Oct 4, 2013 at 14:30. chl. 54.2k 23 225 385. asked Oct 4, 2013 at 14:21. abhijit. 11 1 2. 3. Of possible interest: Assessing reliability of a questionnaire: dimensionality, problematic items, and whether to use alpha, lambda6 or some other index?, Omega vs. alpha reliability. – chl.