Comparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.

When estimating the influence of sentence complexity on reading, researchers typically opt for one of two main approaches: Measuring syntactic complexity (SC) or transitional probability (TP). Comparisons of the predictive power of both approaches have yielded mixed results. To address this inconsis...

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Autores principales:	Bob Kapteijns, Florian Hintz
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f42f9cebcfef48448b5ba94a975ab2ad
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spelling	oai:doaj.org-article:f42f9cebcfef48448b5ba94a975ab2ad2021-12-02T20:15:26ZComparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.1932-620310.1371/journal.pone.0254546https://doaj.org/article/f42f9cebcfef48448b5ba94a975ab2ad2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254546https://doaj.org/toc/1932-6203When estimating the influence of sentence complexity on reading, researchers typically opt for one of two main approaches: Measuring syntactic complexity (SC) or transitional probability (TP). Comparisons of the predictive power of both approaches have yielded mixed results. To address this inconsistency, we conducted a self-paced reading experiment. Participants read sentences of varying syntactic complexity. From two alternatives, we selected the set of SC and TP measures, respectively, that provided the best fit to the self-paced reading data. We then compared the contributions of the SC and TP measures to self-paced reading times when entered into the same model. Our results showed that while both measures explained significant portions of variance in reading times (over and above control variables: word/sentence length, word frequency and word position) when included in independent models, their contributions changed drastically when SC and TP were entered into the same model. Specifically, we only observed significant effects of TP. We conclude that in our experiment the control variables explained the bulk of variance. When comparing the small effects of SC and TP, the effects of TP appear to be more robust.Bob KapteijnsFlorian HintzPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0254546 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bob Kapteijns Florian Hintz Comparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.
description	When estimating the influence of sentence complexity on reading, researchers typically opt for one of two main approaches: Measuring syntactic complexity (SC) or transitional probability (TP). Comparisons of the predictive power of both approaches have yielded mixed results. To address this inconsistency, we conducted a self-paced reading experiment. Participants read sentences of varying syntactic complexity. From two alternatives, we selected the set of SC and TP measures, respectively, that provided the best fit to the self-paced reading data. We then compared the contributions of the SC and TP measures to self-paced reading times when entered into the same model. Our results showed that while both measures explained significant portions of variance in reading times (over and above control variables: word/sentence length, word frequency and word position) when included in independent models, their contributions changed drastically when SC and TP were entered into the same model. Specifically, we only observed significant effects of TP. We conclude that in our experiment the control variables explained the bulk of variance. When comparing the small effects of SC and TP, the effects of TP appear to be more robust.
format	article
author	Bob Kapteijns Florian Hintz
author_facet	Bob Kapteijns Florian Hintz
author_sort	Bob Kapteijns
title	Comparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.
title_short	Comparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.
title_full	Comparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.
title_fullStr	Comparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.
title_full_unstemmed	Comparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.
title_sort	comparing predictors of sentence self-paced reading times: syntactic complexity versus transitional probability metrics.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/f42f9cebcfef48448b5ba94a975ab2ad
work_keys_str_mv	AT bobkapteijns comparingpredictorsofsentenceselfpacedreadingtimessyntacticcomplexityversustransitionalprobabilitymetrics AT florianhintz comparingpredictorsofsentenceselfpacedreadingtimessyntacticcomplexityversustransitionalprobabilitymetrics
_version_	1718374620346712064

Comparing predictors of sentence self-paced reading times: Syntactic complexity versus transitional probability metrics.

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