This study compares the performance of three nonparametric item characteristic curve (ICC) estimation procedures: isotonic regression, smoothed isotonic regression, and kernel smoothing. Smoothed isotonic regression, employed along with an appropriate kernel function, provides better estimates and also satisfies the assumption of strict monotonicity. As the number of items and the sample size increase, the kernel smoothing and smoothed isotonic regression ICC estimation procedures yield similar results across all conditions.
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