How prevalent is dyslexia? A definitive answer to this question has been elusive because of the continuous distribution of reading performance and predictors of dyslexia and because of the heterogeneous nature of samples of poor readers. Samples of poor readers are a mixture of individuals whose reading is consistent with or expected based on their performance in other academic areas and in language, and individuals with dyslexia whose reading is not consistent with or expected based on their other performances. In the present article, we replicate and extend a new approach for determining the prevalence of dyslexia. Using model-based meta-analysis and simulation, three main results were found. First, the prevalence of dyslexia is better represented as a distribution that varies as a function of severity as opposed to any single-point estimate. Second, samples of poor readers will contain more expected poor readers than unexpected or dyslexic readers. Third, individuals with dyslexia can be found across the reading spectrum as opposed to only at the lower tail of reading performance. These results have implications for screening and identification, and for recruiting participants for scientific studies of dyslexia.

中文翻译：

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阅读障碍的患病率：一种新的估计方法

阅读障碍有多普遍？由于阅读成绩和阅读障碍预测因素的连续分布以及不良读者样本的异质性，这个问题的明确答案一直难以捉摸。阅读能力差的样本包括阅读能力与其在其他学术领域和语言方面的表现一致或预期的个体，以及阅读困难的个体，其阅读能力与其其他表现不一致或预期不一致。在本文中，我们复制并扩展了一种确定阅读障碍患病率的新方法。使用基于模型的荟萃分析和模拟，发现了三个主要结果。首先，阅读障碍的患病率可以更好地表示为随严重程度变化的分布，而不是任何单点估计。其次，不良读者的样本中包含的预期不良读者将多于意外或有阅读困难的读者。第三，患有阅读障碍的人可以在整个阅读范围内找到，而不是只在阅读表现的低端。这些结果对于筛查和识别以及招募参与者进行阅读障碍科学研究具有重要意义。