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Each relative clause ended in a lexical verb followed by an auxiliary whereas the main clause ended in a lexical verb only because the main-clause auxiliary occurred already in the second position of the sentence. Sentences in the condition ��embedded clause�� contained one more level of embedding and thus consisted of four clauses: a short main clause, a complement clause (S1) and two center-embedded relative clauses (S2 and S3). The short main clause always preceded the complement clause. In complete sentences, all three verbs were present. In missing-VP sentences, either VP2 (lexical verb and auxiliary) or VP1 [lexical verb and auxiliary in the condition ��embedded clause�� and just lexical verb in the condition ��main cause,�� in which the auxiliary appeared in the main clause, cf. (15)] was missing. The lexical verbs in VP1 and VP2 were always compatible with an animate subject and insofar compatible with both S1 and S2. However, their syntactic properties prevent them from being interchangeable: V1 was an intransitive verb while V2 was transitive. The sentences were distributed across six lists using a Latin square design. Each list contained only a single version of each sentence and an equal number of sentences in each condition. The experimental lists were interspersed in a list of about 260 filler sentences for Experiment 1. The majority of filler sentences was from unrelated experiments. Each participant saw only one list. 5.1.3. Procedure Participants received a questionnaire on which the experimental sentences were printed. They were asked to judge the grammaticality of each sentence on the questionnaire by marking one of the two options ��grammatical�� or ��ungrammatical�� printed beneath each sentence. Participants could spend as much time as they wanted on reading the sentences and giving their judgments. On average, they needed about 45�C50 min to complete the questionnaire. 5.2. Results For each participant and item, we recorded the grammaticality judgment. Table ?Table11 shows the results in terms of acceptance rates. All statistical analyses reported in this paper were computed using the statistics software R, version 2.14.2 (R Development Core Team, 2012). Responses were analyzed by means of linear mixed-effects logistic regression using the R-package lme4 (Bates and Maechler, 2010). Forward difference BGB324 coding was used for the experimental factors. That is, they were coded in such a way that all contrasts tested whether the means of adjacent factor levels were significant. Contrasts were specified as follows. For the factor Clause Type, the mean results in the condition ��main clause�� are contrasted with the mean results in the condition ��embedded clause.�� For the factor Structure, two contrasts were defined.