title: The role of developmental levels in examining the effect of subject types on the production of auxiliary is in young english-speaking children.
abstract: OBJECTIVE
  Prior work (Guo, Owen, & Tomblin, 2010) has shown that at the group level, auxiliary is production by young English-speaking children was symmetrical across lexical noun and pronominal subjects. Individual data did not uniformly reflect these patterns. On the basis of the framework of the gradual morphosyntactic learning (GML) hypothesis, the authors tested whether the addition of a theoretically motivated developmental measure, tense productivity (TP), could assist in explaining these individual differences.
  
  
  METHODS
  Using archival data from 20 children between age 2;8 and 3;4 (years;months), the authors tested the ability of 3 developmental measures (TP; finite verb morphology composite, FVMC; mean length of utterance, MLU) to predict use of auxiliary is with different subject types.
  
  
  RESULTS
  TP, but not MLU or FVMC, significantly improved model fit. Children with low TP scores produced auxiliary is more accurately with pronominal subjects than with lexical subjects. The facilitative effect of pronominal subjects on the production of auxiliary is, however, was not found in children with high TP scores.
  
  
  CONCLUSIONS
  The finding that the effect of subject types on the production accuracy of auxiliary is changed with children's TP is consistent with the GML hypothesis.
authors.affiliation: University at Buffalo, The State University of New York, USA. lingyugu@buffalo.edu
authors.forename: Ling-Yu
authors.initials: LY
authors.lastname: Guo
authors.forename: Amanda J
authors.initials: AJ
authors.lastname: Owen Van Horne
authors.forename: J Bruce
authors.initials: JB
authors.lastname: Tomblin
mesh_terms: D002663:Child Language; D002675:Child, Preschool; D016208:Databases, Factual; D005260:Female; D006801:Humans; D007802:Language; D007804:Language Development; D007807:Language Tests; D008037:Linguistics; D008297:Male; D008962:Models, Theoretical; D012044:Regression Analysis; D013060:Speech