less easily comprehensible), following Jaeger (2008). We used the statistical Galunisertib mw software R (version 2.15.2, R Core Team., 2013) with the supplied lme4 package ( Bates, Maechler, & Dai, 2009) for the mixed models analysis and the ggplot2 package ( Wickham, 2009) for the display of the results. To analyze the categorical judgments using logit mixed models, CONTEXT TYPE, WORD ORDER and the interaction of both were defined as fixed effects, while participants and items were defined as random effects. Fixed effects were coded as +.5/−.5 contrasts resembling traditional ANOVA analyses. Model fitting started with the most complex model ( Barr, Levy, Scheepers, & Tily, 2013); that is, with the

this website full factorial set of random effects (random slope adjustments for all fixed effects for both participants and items). In a step-wise manner, the complex model was reduced by model comparisons via log-likelihood tests (e.g., Baayen, 2008 and Baayen et al., 2008). Slope adjustments were excluded if they did not improve the explanatory power of the model in comparison to the simpler model without that slope adjustment. Logit mixed models were fitted by the Laplace approximation. Estimates (b), standard errors (SE), z-values and the level of significance (p) of the final logit mixed model are reported. Participants showed the following mean (M)

proportion for stories judged as easily comprehensible per condition: NEUTRAL SO: M = 0.93 (SE = 0.04), TOPIC SO: M = 0.92 (SE = 0.04), NEUTRAL OS: M = 0.37 (SE = 0.05), TOPIC

OS: M = 0.54 (SE = 0.05) (see Fig. 1). The statistical analysis of the participants’ categorical judgments of the until stories revealed significant main effects of CONTEXT TYPE and WORD ORDER, and a significant interaction of CONTEXT TYPE × WORD ORDER (see Table 2 for statistics of the final logit mixed models).2 Post hoc logit mixed models to resolve the interaction within each WORD ORDER revealed a significant effect of CONTEXT TYPE for stories containing OS sentences, but not for stories containing SO sentences. Thus, stories containing the OS target sentence were more likely to be judged as easily comprehensible if presented together with the TOPIC CONTEXT. For stories containing the SO target sentence, the probability to be judged as easily comprehensible was equally high independent of the preceding CONTEXT TYPE and significantly higher than for stories with the OS target sentence. In Experiment 2, participants were presented with the same stories as in Experiment 1, while ERPs were used to investigate the effect of the preceding discourse context (CONTEXT TYPE: TOPIC vs. NEUTRAL) during online processing of German SO and OS sentences. Simultaneously, the behavioral performance of the participants was monitored in the form of a sentence-picture-verification task administered in 20% of the trials.