Table 7.
Mean adjusted score (standard error) on the mispronunciation detection task with Bayes inclusion factors and interpretations with nonverbal intelligence as a covariate.
| Word length | Phonological similarity | Visual similarity | Location | Orthography | Verbs |
|---|---|---|---|---|---|
| Monolingual | |||||
| 49.1 (2.3) | 32.3 (2.1) | 45.1 (2.1) | 44.4 (2.5) | 49.6 (2.7) | 38.7 (2.5) |
| n = 159 | n = 162 | n = 162 | n = 160 | n = 132 | n = 155 |
|
Bilingual | |||||
| 39.0 (3.6) | 21.8 (2.9) | 28.1 (3.5) | 28.8 (3.3) | 34.5 (3.4) | 30.0 (3.4) |
| n = 76 | n = 75 | n = 76 | n = 76 | n = 71 | n = 73 |
|
Bayes inclusionary factor | |||||
| Groups tend to not differ (BFINC = 0.34, anecdotal) Interaction is null (BFINC = 0.20, moderate) |
Groups tend to not differ (BFINC = 0.65, anecdotal) Interaction is null (BFINC = 0.17, moderate) |
Groups differ (BFINC = 18.53, strong) Interaction suggests null hypothesis (BFINC = 0.45, anecdotal) |
Groups differ (BFINC = 10.36, strong) Interaction is null (BFINC = 0.23, moderate) |
Groups differ (BFINC = 12.55, strong) Interaction is null (BFINC = 0.19, moderate) |
Groups tend to not differ (BFINC = 0.41, anecdotal) No interactions possible in this game |
Note. We checked for interactions but reported the findings for the strongest model that included group. The Bayes inclusion factor “…compares models that contain the effect to the equivalent models stripped of the effect.” (JASP 0.8.6), an analysis suggested by S. Mathôt (Wagenmakers et al., 2018).