This study presents and evaluates a method of standardization that may be used by test practitioners to standardize classical item statistics when sample sizes are small. The effectiveness of this standardization approach was compared through simulation with the one-parameter logistic (1PL) and three parameter logistic (3PL) models based on the criteria of the Pearson product-moment correlation, the mean square error, variance, and squared bias. In light of estimating the item difficulty values, the differences of the performance between the 3PL and standardization methods were small, but the differences between the 1PL and these two methods were large. For the estimation of point biserial correlations, the 3PL model seemed to perform better than the standardization method, and the standardization method performed better than the 1PL model. Although the standardization method did not outperform the 3PL model for the design considered in this study, it could be promising when smaller sample sizes are used. This method may be recommended for use in conjunction with the item response models for the test development when the pretesting sample sizes are small. By employing the classical measurement framework to obtain pretest item statistics, the problem of inaccurate item response theory parameter estimates when limited calibration sample sizes are available can be avoided. (Contains 4 tables and 16 references.) (Author/SLD)