Table 3.
Results of GLME model analysis of accuracy rates.
| Variables | Estimate | SE | z | pr (>|z|) |
|---|---|---|---|---|
| Intercept | 9.22 | 2.48 | 3.72 | <0.001 |
| Familiarity | 3.19 | 1.51 | 2.11* | 0.035 |
| Phonological Similarity | 3.06 | 1.38 | 2.22* | 0.027 |
| ContextY | −3.51 | 2.93 | −1.20 | 0.231 |
| Phonological Similarity: ContextY | −9.24 | 3.09 | −2.99** | 0.003 |
| Familiarity: Phonological Similarity: ContextN | 1.26 | 1.11 | 1.14 | 0.256 |
| Familiarity: Phonological Similarity: ContextY | −7.03 | 1.74 | −4.04*** | <0.001 |
*p < 0.05, **p < 0.01, ***p < 0.001.
Participants = 31. Items = 44. Total observation = 1181.
SE, standard error. df, degree of freedom.
The optimal model is glmer [acc ~ Familiarity + Phonological Similarity + Context + Phonological Similarity: Context + Familiarity: Phonological similarity: Context + (1|item) + (1|participant), data = data, glmerControl optimizer = “bobyqa,” optCtrl = list (maxfun = 100000)].