Abstract
Under the minimum logit chi‐square item parameter estimation procedure, observed proportions of correct response of zero or unity result in infinite logits and estimates cannot be obtained. The paper examines the application of three rules (l/2n, l/4n and elimination) for dealing with such cases. A simulation study is conducted in which sample size, number of grouping intervals, underlying item discrimination and difficulty are varied. The outcome variables are the square of the difference between the estimates and the underlying parameter values for item discrimination and difficulty. The results indicate that a complex set of interactions exist among the factors employed in the study. Overall, the 1/4n rule is preferred over the other two rules as it generally yields the smallest RMSE for both item discrimination and difficulty. However, as sample size increases the differences among the three rules decreased.
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