To examine the effect of lexical variables on two-character Chinese compound word processing, we performed item-level hierarchical regression analyses on lexical decision megastudy data of 18,983 two-character Chinese compound words. The first analysis determined the unique item-level variance explained by orthographic (frequency and stroke count), phonological (consistency, homophonic density), and semantic (transparency) variables. Both character and word variables were considered. Results showed that orthographic and semantic variables, respectively, accounted for more collective variance than phonological variables, suggesting that Chinese skilled readers rely more on orthographic and semantic information than phonological information when processing visually presented words. The second analysis tested interactive effects of lexical variables and showed significant semantic transparency × cumulative character frequency and word frequency × cumulative character frequency interactions. The effect of cumulative character frequency was stronger for transparent words than for opaque words and was stronger for low-frequency words than for high-frequency words. However, there was no semantic transparency × word frequency interaction in reaction time. Implications of the current findings on models of Chinese compound word processing are discussed.
The neural basis of compound word processing revealed by varying semantic transparency and morphemic neighborhood size
