SAS proc corr nosimple nocorr nomiss alpha; var q1-q10; run; Cronbach Coefficient Alpha VariablesAlpha Raw0.743825
Cronbach Coefficient Alpha with Deleted Variable Deleted Variable Raw Variables Correlation with TotalAlpha q10.4437950.718348 q20.4411190.717466 q30.6041680.690420 q40.5315200.704966 q50.6226410.694956 q60.3365970.732539 q70.2469740.748538 q80.3082850.736302 q90.4058340.724557 q100.2005490.755307
The Idealism Scale 7. Deciding whether or not to perform an act by balancing the positive consequences of the act against the negative consequences of the act is immoral. 10. Moral actions are those which closely match ideals of the most "perfect" action.
Alpha from Item Variances If nmiss (of Q1-Q10) > 0 then delete; TOT=Q1+Q2+Q3+Q4+Q5+Q6+Q7+Q8+Q9 +Q10; proc means var; var q1-q10 tot; OUTPUT OUT=VarOut VAR=VQ1-VQ10 VTot;
title 'Computing alpha from item variances.'; DATA _NULL_; FILE PRINT; SET VAROUT; SUMVAR = SUM(OF VQ1-VQ10); Alpha = (10/9)*(1-SUMVAR/VTOT); put; put Alpha = ; run; Alpha=0.7438254943
Working with Only First 4 Items Create all three possible split halves A1=Q1+Q2; B1=Q3+Q4; A2=Q1+Q3; B2=Q2+Q4; A3=Q1+Q4; B3=Q2+Q3; Obtain alpha the easy way proc corr nosimple nocorr nomiss alpha; var Q1-Q4; Alpha = 0.716882
Find the 3 Split-Half Corrs proc corr nosimple nomiss; var A1; with B1; proc corr nosimple nomiss; var A2; with B2; proc corr nosimple nomiss; var A3; with B3; r 1 = 0.49581 r 2 = 0.66198 r 3 = 0.53911
Obtain 4 for Each Split Half Apply Spearman-Brown correction The three values are.6629,.7966, and.7005. The mean of these three is.72, Cronbach’s alpha. The highest of these three is maximized 4
Osburn (2000) showed that Cronbach alpha is a conservative estimate of reliability. Maximized 4 is a better estimate. But for 2n items, there are pairs of split halves Ouch. For 10 items, 126 split halves. There are ways to estimate, if you have FORTRAN.