Cronbach's alpha

http://www2.chass.ncsu.edu/garson/pa765/reliab.htm#alpha

• Low cronbach alpha indicates low interitem correlations
• Reliability of a measure is sample specific. Thus, we should report relibility estimates based on responses of our subjects, rather than ones given in the manuals for the measures used or ones reported by other researchers using the same measures.
• Cronbach's alpha coefficient of reliability, an alpha of 0.7 is normally considered to indicate a reliable set of items (de Vaus, 2002)
• Cronbach alpha is a measure of internal consistency, it is not a measure of unidimensionality and can't be used to infer unidimensionality. Danes,J.E. & Mann, O.K. (1984) Unidimensional measurement and strucutral equation models with latent variables. Journal of Business Research, 12: 337-352
• with multi-item measures, the internal consistency measure is the best reliability test. Of the internal consistency measures, Cronbach's alpha is the most widely used.
• How to get Cohen's Kappa in SPSS-- analyze--descriptive statistics--crosstabs--row (input y variables)--colume (input x variables)--suppress tables--statistics--choose "Kapph" -- continue--OK
• How to get inter-item correlatons in SPSS--analyze--scale--reliability analysis--items(input list of items to be correlated)--model (Alpha)--statistic --inter-item--correlations--continue--OK
• Howe to get item-total correlations in SPSS-- analyze--scale--reliability analysis--items (input items to be correlated)--model (alpha)--statistics--inter-item--correlations--descriptives for -- scale if item deleted -- continue--OK
• How to get Cronbach's alpha in SPSS--analyze--scale--reliability analysis--input (input list of items to be correlated)--model (alpha)--statistics--descriptives for --scale if item deleted--continue--OK
• If the variables being tested are all dichotomous, Cronbach's alpha is the same as Kuder-Richardson coefficient
• Random error affects the degree of reliability. The greater the random error, the less reliabile the measure. Where there is very little random error, the measure is reliable. de Vaus, D. (2002). Analyzing social science data. London, Sage.
  
• Cronbach's alpha (the reliability coefficient) Cronbach's alpha is a measure of the intercorrelation of items; the estimate of internal consistency of items in a scale, measuring the extent to which item responses obtained at the same time correlate highly with each other. Alpha equals zero when the true score is not measured at all and there is only an error component. Alpha equals 1.0 when all items measure only the true score and there is no error component. The widely-accepted social science cut-off is that alpha should be .70 or higher for a set of items to be considered a scale, but some use .75 or .80 while others are as lenient as .60. That .70 is as low as one may wish to go is reflected in the fact that when alpha is .70, the standard error of measurement will be over half (0.55) a standard deviation.
• Cronbach's alpha increases as the number of items in the scale increases. Increasing the number of items can be a way to push alpha to an acceptable level. This reflects the assumption that scales and instruments with a greater number of items are more reliable. It also means that comparison of alpha levels between scales with differing numbers of items is not appropriate.
• The squared multiple correlation. R2 is the R2 for an item when it is predicted from all other items in the scale. The larger the R2, the more the item is contributing to internal consistency. The lower the R2, the more the researcher should consider dropping it. Note the R2 of some items may be low even on a scale which has an acceptable Cronbach's alpha overall.
• Negative alphas. Note also that a negative Cronbach's alpha indicates inconsistent coding (see assumptions) or a mixture of items measuring different dimensions, leading to negative inter-item correlations.
• The Kuder-Richardson (KR20) coefficient is the same as Cronbach's alpha when items are dichotomous.
• In SPSS, Cronbach's alpha is found under Analyze, Scale, Reliability Analysis. Then in the Statistics button, check Scale to get alpha. You can also check Scale if deleted, in which case alpha will be computed both for all variables entered, and also for all remaining variables if any one is dropped (the alpha if deleted is listed in a table, one for each variable). That is, the 'scale if deleted' option lets the researcher assess the reliability of each item.
• Alpha if deleted. SPSS will compute "Cronbach's Alpha if Item Deleted," which is the estimated value of alpha if the given item were removed from the model. The researcher may wish to drop items where the alpha if deleted is higher than the overall alpha as another way to improve the alpha level. Note, however, that when an item has high random error it is possible that it would be removed on this basis when, in fact, it does measure the same construct.
• The item-total correlation, also part of SPSS output in the Total Correlation column when Item is checked under the Statistics button. This is the Pearsonian correlation of the item with the total of scores on all other items. A low item-total correlation means the item is little correlated with the overall scale (ex., < .3 for large samples or not significant for small samples) and the researcher should consider dropping it. A negative correlation indicates the need to recode the item in the opposite direction. The reliability analysis should be re-run if an item is dropped or recoded. Note a scale with an acceptable Cronbach's alpha may still have one or more items with low item-total correlations.
• Uncorrelated error. Errors should be uncorrelated