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This study proposes a two-part model that includes components for readingaccuracy and reading speed. The speed component is a log-normal factor model,for which speed data are measured by reading time for each sentence beingassessed. The accuracy component is a binomial-count factor model, where theaccuracy data are measured by the number of correctly read words in eachsentence. Both underlying latent components are assumed to be Gaussian innature. In this paper, the theoretical properties of the proposed model aredeveloped and an Monte Carlo EM algorithm for model fitting is outlined. Thepredictive power of the model is illustrated in a real data application.

An EM Algorithm for Estimating an Oral Reading Speed and Accuracy Model