A Monte Carlo study of factors affecting three indices of composite scale reliability

In a Monte Carlo study, the number of response categories, number of items, covariance among items, and item "error" were varied to simulate scores following classical true score assumptions. Despite considerable literature examining the optimal number of response categories, this variable...

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Bibliographic Details
Published in:Journal of applied psychology 1977-08, Vol.62 (4), p.392-398
Main Authors: Jenkins, G. Douglas, Taber, Thomas D
Format: Article
Language:English
Subjects:
Human
Item Analysis (Statistical)
Monte Carlo simulation
Reliability
Scaling (Testing)
Statistical Reliability
Studies
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Summary:In a Monte Carlo study, the number of response categories, number of items, covariance among items, and item "error" were varied to simulate scores following classical true score assumptions. Despite considerable literature examining the optimal number of response categories, this variable accounted for very little variance in the correlation of fallible composite scale scores and known "true" scores. In no situation did correlations substantially increase with the use of more than 5 response categories. The effects of the 4 variables were largely additive. The relative importance of the variables differed, however, according to whether an internal consistency or a stability estimate was used as the dependent variable. Results are discussed in terms of possible trade-offs for applied researchers.
ISSN:0021-9010
1939-1854
DOI:10.1037/0021-9010.62.4.392