A blind spot in correct naming latency analyses.

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Bibliographic Details
Title: A blind spot in correct naming latency analyses.
Authors: Oppenheim, Gary M. (AUTHOR)
Source: Cognitive Neuropsychology. Feb/Mar2017, Vol. 34 Issue 1/2, p33-41. 9p.
Subjects: Speech errors, Onomasiology, Language & languages, Computational linguistics, Information retrieval
Abstract: Speech errors and naming latencies provide two complementary sets of behavioural data for understanding language production processes. A recent analytical trend—applied to intact and impaired production alike—highlights a link between specific features of correct picture naming latency distributions and the retrieval processes thought to underlie them. Although chronometric approaches to language production typically consider correct response times in isolation, adequately accounting for their distributions in error-prone situations requires also considering the errors that sometimes censor them. In this paper, I illustrate by simulation how excluding incorrect word retrievals predictably alters observed distributions of correct naming latencies. To the extent that naming errors impose a stochastic deadline on successful production, their censoring should tend to reduce the mean, variance, and skew of observed latencies for correct responses, relative to the uncensored underlying distribution. [ABSTRACT FROM AUTHOR]
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Database: Psychology and Behavioral Sciences Collection
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Abstract:Speech errors and naming latencies provide two complementary sets of behavioural data for understanding language production processes. A recent analytical trend—applied to intact and impaired production alike—highlights a link between specific features of correct picture naming latency distributions and the retrieval processes thought to underlie them. Although chronometric approaches to language production typically consider correct response times in isolation, adequately accounting for their distributions in error-prone situations requires also considering the errors that sometimes censor them. In this paper, I illustrate by simulation how excluding incorrect word retrievals predictably alters observed distributions of correct naming latencies. To the extent that naming errors impose a stochastic deadline on successful production, their censoring should tend to reduce the mean, variance, and skew of observed latencies for correct responses, relative to the uncensored underlying distribution. [ABSTRACT FROM AUTHOR]
ISSN:02643294
DOI:10.1080/02643294.2017.1338563