This study compared seven syntactic measures which can be automatically generated by the Computerized Profiling (CP) software: Mean Length of Utterance in morphemes or words (MLUm or MLUw), Mean Syntactic Length (MSL), the Index of Productive Syntax (IPSyn), the Picture Elicited Scoring Procedure (PESP) for the Language Analysis Remediation and Screening Profile (LARSP), the Syntactic Complexity Score (MSC) scoring of LARSP, and Developmental Sentence Scoring (DSS). Language samples came from 192 children, 106 typically developing children, ages 5;6 to 11;2 and 86 children with language impairment, ages 5;6 to 11;1. Patterns of correlation were consistent for children with or without language impairment. All measures were computed with CP software, and all coding decisions that were made by the software were accepted. The three measures of length (MLUm, MLUw, and MSL) were highly intercorrelated. MSC correlated with the measures of length and with DSS. DSS correlated with the length measures, though not as highly as MSC. DSS also correlated with IPSyn. IPSyn correlated moderately with PESP, correlated less with MSC, and correlated the least with the measures of length. PESP correlated moderately with each measure. PESP, DSS, and IPSyn correlated more highly for the children with language impairment. These measures correlated highly sometimes and sometimes they did not correlate much. This suggests that they are measuring different aspects of syntactic ability.

A variety of tools have been developed to assist in the quantification and analysis of naturalistic language samples. In recent years, computer technology has been employed in language sample analysis. This study compares a new automated index, Scoring Sentences Developmentally (SSD), to two existing measures. Eighty samples from three corpora were manually analyzed using DSS and MLU and the processed by the automated software. Results show all three indices to be highly correlated, with correlations ranging from .62 to .98. The high correlations among scores support further investigation of the psychometric characteristics of the SSD software to determine its clinical validity and reliability. Results of this study suggest that SSD has the potential to compliment other analysis procedures in assessing the language development of young children.