Facilitatory interference effect data used for estimating parameters of the LV05 model.
| Dataset . | Number of Participants . | Interference Effect (in milliseconds) . |
|---|---|---|
| Subject-verb agreement dependency | ||
| Dillon et al. (2013) Exp 1 | 40 | −60 [−111, −11] |
| Jäger et al. (2020) | 181 | −27 [−47, 2] |
| Lago et al. (2015) Exp 1 | 32 | −27 [−55, 0] |
| Lago et al. (2015) Exp 2 | 32 | −23 [−54, 7] |
| Lago et al. (2015) Exp 3a | 32 | −13 [−29, 2] |
| Lago et al. (2015) Exp 3b | 32 | −13 [−33, 6] |
| Wagers et al. (2009) Exp 2 | 28 | −23 [−49, 1] |
| Wagers et al. (2009) Exp 3 (Singular subject) | 60 | −18 [−46, 9] |
| Wagers et al. (2009) Exp 3 (Plural subject) | 60 | −4 [−39, 30] |
| Wagers et al. (2009) Exp 4 | 44 | −28 [−53, −3] |
| Wagers et al. (2009) Exp 5 | 60 | −20 [−44, −4] |
| Antecedent-reflexive dependency | ||
| Dillon et al. (2013) Exp 1 | 40 | −18 [−73, 36] |
| Jäger et al. (2020) | 181 | −23 [−49, 2] |
| Dataset . | Number of Participants . | Interference Effect (in milliseconds) . |
|---|---|---|
| Subject-verb agreement dependency | ||
| Dillon et al. (2013) Exp 1 | 40 | −60 [−111, −11] |
| Jäger et al. (2020) | 181 | −27 [−47, 2] |
| Lago et al. (2015) Exp 1 | 32 | −27 [−55, 0] |
| Lago et al. (2015) Exp 2 | 32 | −23 [−54, 7] |
| Lago et al. (2015) Exp 3a | 32 | −13 [−29, 2] |
| Lago et al. (2015) Exp 3b | 32 | −13 [−33, 6] |
| Wagers et al. (2009) Exp 2 | 28 | −23 [−49, 1] |
| Wagers et al. (2009) Exp 3 (Singular subject) | 60 | −18 [−46, 9] |
| Wagers et al. (2009) Exp 3 (Plural subject) | 60 | −4 [−39, 30] |
| Wagers et al. (2009) Exp 4 | 44 | −28 [−53, −3] |
| Wagers et al. (2009) Exp 5 | 60 | −20 [−44, −4] |
| Antecedent-reflexive dependency | ||
| Dillon et al. (2013) Exp 1 | 40 | −18 [−73, 36] |
| Jäger et al. (2020) | 181 | −23 [−49, 2] |
Note. The table lists the published datasets along with the number of participants and population-level mean interference effect. The square brackets show 95% credible intervals around the population-level interference effects, that is, there is a 95% probability that the value of the population-level interference effect lies within this range, given the statistical model and data.