2019
DOI: 10.1037/xlm0000655
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The impact of text orientation on form priming effects in four-character Chinese words.

Abstract: Does visuospatial orientation influence repetition and transposed character (TC) priming effects in logographic scripts? According to perceptual learning accounts, the nature of orthographic (form) priming effects should be influenced by text orientation (Dehaene, Cohen, Sigman, & Vinckier, 2005; Grainger & Holcomb, 2009). In contrast, Witzel, Qiao, and Forster's (2011) abstract letter unit account argues that the mechanism responsible for such effects acts at a totally abstract orthographic level (i.e., the v… Show more

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Cited by 21 publications
(24 citation statements)
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“…We decided to use the generalised linear mixed-effects model and analyse raw RTs rather than the more common practice of using linear mixed-effects models and normalising raw RTs with a reciprocal transformation (e.g., invRT = −1000/RT). The reason is that nonlinear transformations systematically alter the pattern and size of interaction effects, rendering such transformations inappropriate when the research interest lies in interactions, as in the present case (Balota et al, 2013; Cohen-Shikora, Suh, & Bugg, 2018; Yang, Chen, Spinelli, & Lupker, 2019). 1…”
Section: Resultsmentioning
confidence: 92%
“…We decided to use the generalised linear mixed-effects model and analyse raw RTs rather than the more common practice of using linear mixed-effects models and normalising raw RTs with a reciprocal transformation (e.g., invRT = −1000/RT). The reason is that nonlinear transformations systematically alter the pattern and size of interaction effects, rendering such transformations inappropriate when the research interest lies in interactions, as in the present case (Balota et al, 2013; Cohen-Shikora, Suh, & Bugg, 2018; Yang, Chen, Spinelli, & Lupker, 2019). 1…”
Section: Resultsmentioning
confidence: 92%
“…That is, could there be a single model framework involving a letter position coding process that could produce little, if any, transposed letter priming effects in some languages (e.g., Hebrew, Korean), some transposed letter priming effects in others, as long as the transpositions are not extreme (e.g., English, Spanish), and a backward priming effect in others (e.g., Chinese)? And, further, if such a model framework could do so, could that same system be able to explain how it is possible to observe a 50+ ms backward priming effect in Chinese (suggesting that the system makes little effort to produce accurate position coding), while at the same time explaining the 80-ms identity priming effect reported by Yang et al (2019), an effect showing that there is a clear advantage of having the Chinese characters in the same order in the prime and target. Although building such a system is beyond the scope of the present paper, it may be useful to consider the nature of the orthographic coding models currently available in an attempt to get some idea of whether such a system could be built based on the structure of one of them.…”
Section: Models Of Orthographic Codingmentioning
confidence: 99%
“…More recently, Yang and colleagues (Yang et al, 2019;Yang et al, 2020) have provided an examination of extreme transposition priming in Chinese. Those authors demonstrated that, using four-character Chinese words as targets, primes that were the targets written backwards (i.e., using the Roman alphabet to reflect this relationship, it would be "dcba" priming ABCD) produce 50+ ms priming effects, although those effects were still significantly smaller than the identity priming effect that Yang et al (2019) reported (i.e., abcd-ABCD -80 ms).…”
mentioning
confidence: 99%
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“…For instance, developing readers produced significant honse-HOUSE type priming effects for words with large orthographic neighborhoods (Coltheart, Davelaar, Jonasson, & Besner, 1977), whereas skilled adult readers did not (Castles, Davis, & Letcher, 1999). As a second example, transposed-letter nonwords (hosue-HOUSE) produce larger priming effects than substituted-letter nonwords (honae-HOUSE) in many different languages (Perea & Lupker, 2003Yang, Chen, Spinelli, & Lupker, 2019).…”
Section: Introductionmentioning
confidence: 99%