Analysis of error rates

In the NP naming condition, determiner errors, or put differently, gender errors, were analyzed.

Since contrary to the RT analysis no subjects had to be excluded due to missing observations, the analysis was based on 43 subjects. There were 21 high-proficient subjects and 22 low-proficient subjects. 21 of them had participated first in the LDT and 22 first in the PNT. Translation errors and unknown items as assessed in the translation task were removed per participant before analysis. No items were excluded so that the analysis was based on all 114 items.

Correct Incorrect % incorrect

Low- proficient Congruent 796 9 1.1 %

Incongruent 751 26 3.3 %

Incongruent n 790 27 3.3 %

High-proficient Congruent 735 5 0.7 %

Incongruent 707 5 0.7 %

Incongruent n 723 13 1.8 %

Table 4.22 Amount of absolute correct and incorrect determiner productions, and percentage of incorrect productions, across Gender Compatibility conditions, for each proficiency group.

Figure 4.9 Overall percentage of error rates in determiner production per Gender Compatibility condition.

Looking at the descriptive data shown in Table 4.22 and Figure 4.9, it seems as if the tendency of article errors across Gender Compatibility conditions goes into the expected directions for both proficiency groups, that is, more errors are committed in the two incongruent conditions than in the

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4.3 Results PNT

congruent condition. However, it has to be noted that the overall error rate regarding determiners was very low: Overall, only 85 determiner errors were observed, which is less than one error per subject per condition.

Statistical analyses revealed that the differences across Gender Compatibility conditions were significant in the F1-analysis (F1(2, 82) = 4.812, p = 0.015, F2(2, 111) = 1.252, p = 0.290). T-tests (all one-tailed²⁵ and Bonferroni-corrected) revealed that the difference between the congruent and incongruent condition was not significant (t1 = -1.761, df = 42, p = 0.129; t2 = -1.627, df = 74, p = 0.162), the difference between the congruent and incongruent neutral condition was only significant for t1 (t1 = -3.355, df = 42, p = 0.003; t2 = -1.338, df = 74, p = 0.282) and the difference between the incongruent and incongruent neutral condition was not significant (t₁ = -1.003, df = 42, p = 0.483; t₂ = -0.459, df = 74, p = 0.972).

There was also a main effect of Level (F1(1, 41) = 7.429, p = 0.009, F2(1, 111) = 15.746, p < 0.001) and the interaction of Gender Compatibility with Level was significant in F2 (F1(2, 82) = 2.136, p = 0.133, F2(2, 111) = 3.152 p = 0.047). Follow-up analyses of the interaction of Gender Compatibility with Level revealed that the difference across conditions was only significant in the F1-analysis for both levels (low-proficient group: F1(2, 44) = 3.781, p = 0.043, F2(2, 111) = 1.717 p = 0.184; high-proficient group:

F1(2, 38) = 4.022, p = 0.026, F2(2, 111) = 1.176 p = 0.312). T-tests (all one-tailed and Bonferroni-corrected) revealed that for the low-proficient group, the difference between the congruent and incongruent condition was marginally significant for t2 (t1 = -2.017, df = 22, p = 0.168; t2 = -2.357, df = 74, p = 0.063). The difference between the congruent and incongruent neutral condition was significant for t1 (t1 = -3.203, df = 22, p = 0.012; t2 = -1.398, df = 74, p = 0.504). The difference between the incongruent and incongruent neutral condition was not significant (t1 = 0.136, df = 22, p = 0.168; t2 = 0.153, df = 74, p = 1.000). For the high-proficient group, the difference between the congruent and incongruent condition was not significant (t1 = -0.112, df = 19, p = 1.000;

t2 = 0.000, df = 74, p = 1.000) and neither was the difference between the congruent and incongruent neutral condition (t1 = -2.064, df = 19, p = 0.159; t2 = -1.144, df = 74, p = 0.771). The difference between the incongruent and incongruent neutral condition was significant for t1 (t1 = -2.880, df = 19, p = 0.030; t2 = -1.211, df = 74, p = 0.696).

However, due to the low error rate (barely one error per subject per condition) also the significant results have to be interpreted with caution.

Bilingual Spanish group

The analysis was based on 38 subjects. There were 20 high-proficient subjects and 18 low-proficient subjects. 18 of them had participated first in the LDT and 20 first in the PNT. As before, translation errors and unknown items as assessed in the translation task were removed per participant before analysis. No items were excluded so that the analysis was based on all 114 items.

As can be seen in Table 4.23 and Figure 4.10, the amount of errors in determiner production differs across conditions, with the least amount of errors in the congruent condition and more errors committed in the two incongruent condition. This is according to the predictions (cf. section 4.1.2).

The total number of determiner errors was 419.

25 Here and in later places, one-tailed t-tests will be carried out whenever a hypothesis is clearly directional. In this case, e.g., the hypothesis was directional because more errors were expected for cognates than for noncognates, due to the lower frequency and lower transparency of the experimental cognate items.

Correct Incorrect % incorrect

Low- proficient Congruent 570 70 10.9 %

Incongruent 512 83 13.9 %

Incongruent n 550 89 13.9 %

High-proficient Congruent 692 43 5.9 %

Incongruent 635 51 7.4 %

Incongruent n 641 83 11.5 %

Table 4.23 Amount of absolute correct and incorrect determiner productions, and percentage of incorrect productions, across Gender Compatibility conditions, for each proficiency group.

Figure 4.10 Overall percentage of error rates in determiner production per Gender Compatibility condition.

Statistical analyses revealed that the effect of Gender Compatibility was significant in the F₁-analysis (F₁(2, 72) = 6.830, p = 0.004, F₂(2, 110) = 2.223, p = 0.113). T-tests (all one-tailed and Bonferroni-corrected) revealed that the difference between the congruent and incongruent condition was marginally significant in the t1-analysis (t1 = -2.448, df = 37, p = 0.057; t2 = -0.792, df = 74, p = 1.000), the difference between the congruent and incongruent neutral condition was significant for t1 and marginally significant for t2 (t1 = -3.106, df = 37, p = 0.012; t2 = -2.208, df = 74, p = 0.090) and the difference between the incongruent and incongruent neutral condition was not significant (t1 = -1.842, df = 37, p = 0.219; t2 = -1.318, df = 74, p = 0.577).

There was also a main effect of Level (F1(1, 36) = 8.133, p = 0.007, F2(1, 110) = 32.125, p < 0.001). The interaction of Gender Compatibility with Level was not significant (F1(2, 72) = 1.868, p = 0.170, F2(2, 110) = 1.747 p = 0.179).

Summary

When looking at the gender errors in the determiner naming condition, the error rates of both the German and the Spanish bilingual group exhibited differences across Gender Compatibility conditions. For both L2 groups, more errors were committed in the two incongruent conditions than in the congruent condition. Statistical analyses revealed that for the German bilingual group, the effect of Gender Compatibility was significant in the F1-analysis. T-tests showed that the difference between the congruent and incongruent condition was marginally significant for t1 and the difference between the congruent and incongruent neutral condition was significant for t1 and marginally significant for t2. The interaction of Gender Compatibility and Level was also significant in the F2 -analysis. Follow-up analyses revealed that the most important comparison between the congruent and incongruent condition was marginally significant for t2 in the low-proficient group and not significant in the high-proficient group. This suggests that transfer occurred in the low-proficient group but not in the high-proficient group. However, due to the low amount of observations (barely one error per subject per condition on average), these results have to be interpreted with caution.

The analysis of the Spanish bilingual error rates revealed a significant effect of Gender Compatibility in the subject-analysis. T-tests showed that the difference between the congruent and incongruent condition was marginally significant in the t1-analysis. The difference between the incongruent and

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congruent incongruentincongruent n Error rate