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The accuracy results were analyzed using a Bayesian mixed effects logistic regression model with listener language group (Monolingual, Early Bilingual, Late Bilingual), stimulus language (English, Spanish), and stimulus type (phonemic, phonetic) as fixed effects and participant and stimulus word as random intercepts. The models were fitted via a Markov Chain Monte Carlo procedure using STAN (Gelman et al., 2015). Model comparison was performed using the Deviance Information Criterion (DIC; Spiegelhalter et al., 2002). A model with a three-way interaction among the fixed effects provided an improved fit over models with two-way interactions or with only main effects (see Table ?Table66 for the model summary). The reference group, reflected in the model intercept, represents BKM120 solubility dmso the accuracy of Monolinguals categorizing stimuli with an English phoneme. The fitted log odds of accuracy for each stimulus language and listener language group are plotted in Figure ?Figure11, with the phonemic cues in the left panel and the phonetic cues in the right panel. The error bars represent the 95% Bayesian credible intervals. Table 5 Mean accuracy of each listener group for each stimulus type. Table Oxygenase 6 Summary of mixed effects logistic regression model fitting accuracy results. FIGURE 1 Predicted log odds of accuracy for phonemic and phonetic cues. Comparing Spanish and English Phonemic and Phonetic Cues Overall, listeners responded more accurately to Spanish cues than to English cues, and to phonemic cues than to phonetic cues. The difference between the languages was greater for phonemic cues than for phonetic cues. The Spanish phoneme was categorized more accurately than the English phonemes (Monolinguals: �� = 2.242, posterior SD = 0.459, p Bilinguals trended toward categorizing the English phonemic cues more accurately than the English phonetic cues (�� = 0.448, NU7441 ic50 posterior SD = 0.358, p = 0.09). The Late Bilinguals categorized English phonemic cues significantly better than English phonetic cues (�� = 0.922, posterior SD = 0.358, p
