Building an item bank which most effectively facilitates the evaluation of eligibility for clinical hospital practice in nursing colleges is clearly desirable. However, the 2PL IRT model, commonly used to standardize item parameters, requires more than 300 examinees in order to estimate stable item parameters (Toyoda, 2012). Although Mitsunaga, et al (2014) used some prior distribution to obtain stable item parameters-based estimates from smaller datasets, in practice the relevant prior information is not always available. In this paper, eight CBT test forms were administered to eight groups, each of which had fewer than 200 examinees. To obtain feasible parameter estimates using such small datasets, latent rank theory (LRT; Shojima, 2009) was applied. The results suggest that relatively accurate LRT estimates are possible without any prior distribution. This can be achieved by setting up a group of small datasets which are conducive to IRT analysis where evaluation of item characteristics and examinee ability estimates can be carried out by the comparison of item parameters.
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