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Also note that vocal and manual responses were equally sensitive to lexical effects in other linguistic tasks �Ce.g., word frequency in Hutson et al. (2011). Statistical analysis Invalid responses were eliminated for analysis, but their proportion was previously compared across expertise levels with a Chi square test. Valid data were log transformed to make them amenable to parametric analysis. Within each participant, log (RT) were averaged for each combination of task, cognate status, and concreteness. Those averages were analyzed using a four-way mixed-model analysis of variance (ANOVA) with a between-subject factor with 2 levels of informal translation expertise DMXAA (level: LOW, HI) and 3 within-subjects factors with different levels: task (L1R, L2R, BT, FT), cognate status (Cog, NCog), and concreteness (Abs, Con). The Tukey a posteriori test was used to examine the pairwise comparison for significant ANOVAs. Given the large number of pairwise comparisons, p-values for interactions are reported in the supplementary material (Appendix 4). All analyses were performed using Statistica 10.0 (Statsoft). RESULTS Invalid responses Five exclusion criteria were considered: (i) no 17-DMAG (Alvespimycin) HCl response (e.g., subject remains silent); (ii) hesitation or false start (e.g., fury��fueg�� furia!); (iii) task confusion (e.g., subject reads when asked to translate, or vice versa); (iv) wrong translation (e.g., fury��fuera); and (v) non-predefined translation (e.g., fury�� ira). 4 Across participants, invalid responses varied from 5 (2.0) to 72 (28.1%). The proportion of invalid responses was inversely related with proficiency level (LOW = 22.4%, HI = 8.0%; Chi square (1) = 213.931, p Danusertib purchase number of invalid trials on L2R (p = 0.001), BT (p