By Patrick Doyle

The papers that seem during this detailed variation of Aphasiology have been chosen established upon their theoretical significance, medical relevance, and medical advantage, from among the platform and poster displays comprising the thirty second Annual scientific Aphasiology convention held in Ridgedale, Missouri in June of 2002. every one paper used to be peer-reviewed through the Editorial experts and affiliate Editors stated herein in keeping with the criteria of Aphasiology and the rigours of advantage evaluation that characterize this listed, archival magazine.

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This would allow for comparisons of different sample lengths, as long as equivalent sample segment sizes were used. However, since segment size must be controlled, this measure is still dependent on sample size. , Prins, Snow, & Wagenaar, 1978; Spreen & Wachal, 1973) have produced similar findings relative to the productive vocabulary of adults with aphasia, but they highlight the central weakness of TTR; its sensitivity to sample size variation. More recently, although within the area of child language research, there have been some data to suggest that TTR, when used in the diagnosis of specific language impairment, is not sufficiently sensitive to separate the lexical performance of children with and without language impairments (Watkins, Kelly, Harbers, & Hollis, 1995).

These deficits may present themselves in discourse through the person’s use of nonreferential terminology, pauses, filler terms, paraphasias, or neologisms. Typically, adults with a nonfluent type of aphasia use pauses and filler terms as they struggle with verbal output. By contrast, adults with a fluent type of aphasia have little difficulty with verbal output, although they do produce paraphasias and neologisms during verbal production. Clearly, an important aspect to aphasia assessment is the analysis of discourse production, especially given the fact that many of the above characteristics are primarily detectable through the analysis of discourse.

RESULTS Relationships among D, NDW, and TTR Pearson correlations were performed to determine the possible relationships among D, NDW, and TTR. Because of the number of correlations performed, a Bonferroni adjustment was applied to minimise the probability of Type I error. 001 were considered significant. As shown in the correlation matrix in Table 2, when the samples were truncated to 100 and 200 words, the three measures correlated with each other for each sample length. 001 level. In addition, as shown in the correlation matrix, although each of the three D sample sizes were significantly correlated with each other, this was not the case for the other two measures; correlations between the three sample sizes were observed only once for TTR (between TTR–100 and TTR–200) and twice for NDW (between whole samples NDW and NDW–200, and between NDW–100 and NDW–200).

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