It is shown that the psychometric test reliability, based on any true-score model with randomly sampled items and conditionally independent errors, converges to 1 as the test length goes to infinity, assuming some fairly general regularity conditions. The asymptotic rate of convergence is given by the Spearman-Brown formula, and for this it is not needed that the items are parallel, or latent unidimensional, or even finite dimensional. Simulations with the 2-parameter logistic item response theory model reveal that there can be a positive bias in the reliability of short multidimensional tests, meaning that applying the Spearman-Brown formula in these cases would lead to overprediction of the reliability that will result from lengthening the tests. For short unidimensional tests under the 2-parameter logistic model the reliabilities are almost unbiased, meaning that application of the Spearman-Brown formula in these cases leads to predictions that are approximately unbiased.

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