The effects of heterogeneous item distributions on reliability

A computer simulation was designed to investigate the degree to which coeff icient alpha is affected by the inclusion of items with different distribut ion shapes within a unidimensional scale. Theoretical scales were generated that combined different numbers of normal, moderately skewed, extremely sk ewed, and leptokurtic items. This process was repeated using different numb ers of response categories (3, 5, 7, and 9), and different levels of interi tem correlation (.25, .50, and .75). Results indicated that reliability did not decrease dramatically as a result of utilizing differentially shaped i tems within a scale; the largest decreases came about when utilizing highly skewed items. However, these results were moderated by the correlational s tructure and by the number of response categories. Utilizing differentially shaped items brought about the largest decreases in reliability when the i nteritem correlations were low and when the number of response categories w as small. Conversely, reliability was least affected when the interitem cor relations were high and when the number of response categories was large. I t was suggested that the practice of deleting items from a scale on the bas is of distributional nonnormality may adversely affect scale validity with no appreciable increase in reliability.