Cover not available

Article published In: The Mental Lexicon
Vol. 18:2 (2023) ► pp.218264

References (56)
References
Amenta, S., & Crepaldi, D. (2012). Morphological processing as we know it: An analytical review of morphological effects in visual word identification. Frontiers in Psychology, 31, 1 – 12. Google Scholar logo with link to Google Scholar
Baayen, R. H., Chuang, Y. Y., Shafaei-Bajestan, E., & Blevins, J. P. (2019). The discriminative lexicon: A Unified computational model for the lexicon and lexical processing in comprehension and production grounded not in (de) composition but in linear discriminative learning. Complexity, 2019, 4895891. Google Scholar logo with link to Google Scholar
Baayen, R. H., Dijkstra, T., & Schreuder, R. (1997). Singulars and plurals in Dutch: Evidence for a parallel dual-route model. Journal of Memory and Language, 37(1), 94 – 117. Google Scholar logo with link to Google Scholar
Baayen, R. H., Feldman, L. B., & Schreuder, R. (2006). Morphological influences on the recognition of monosyllabic monomorphemic words. Journal of Memory and Language, 55(2), 290–313. Google Scholar logo with link to Google Scholar
Baayen, R. H. & Renouf, A. (1996). Reading the Times: Productive lexical innovations in an English newspaper. Language, 72(1), 69–96. Google Scholar logo with link to Google Scholar
Balling, L. W., & Baayen, R. H. (2008). Morphological effects in auditory word recognition: Evidence from Danish. Language and Cognitive Processes, 23(7–8), 1159–1190. Google Scholar logo with link to Google Scholar
Bertram, R., Schreuder, R., & Baayen, R. H. (2000). The balance of storage and computation in morphological processing: The role of word formation type, affixal homophony, and productivity. Journal of Experimental Psychology: Learning, Memory, & Cognition, 261, 489–511. Google Scholar logo with link to Google Scholar
Caramazza, A., Laudanna, A., & Romani, C. (1988). Lexical access and inflectional morphology. Cognition, 28(3), 297–332. Google Scholar logo with link to Google Scholar
Chateau, D., Knudsen, E. V. & Jared, D. (2002). Masked priming of prefixes and the influence of spelling-meaning consistency. Brain and Language, 81(1–3), 587–600. Google Scholar logo with link to Google Scholar
Chuang, Y., Fon, J., & Baayen, R. H. (2020). Analyzing phonetic data with generalized additive mixed models. Google Scholar logo with link to Google Scholar
Colé, P., Beauvillain, C., & Segui, J. (1989). On the representation and processing of prefixed and suffixed derived words: a differential frequency effect. Journal of Memory and Language, 281, 1 – 13. Google Scholar logo with link to Google Scholar
De Jong, N., Schreuder, R. & Baayen, R. H. (2000). The morphological family size effect and morphology, Language and Cognitive Processes, 15(4/5), 329–365. Google Scholar logo with link to Google Scholar
Denistia, K., and Baayen, R. H. (2019). The Indonesian prefixes PE- and PEN-: A study in productivity and allomorphy. Morphology, 29(3), 385–407. Google Scholar logo with link to Google Scholar
Denistia, K., & Baayen, R. H. (2021). The morphology of Indonesian: Data and quantitative modeling. In C. Shei (Ed.), The Routledge handbook of Asian linguistics. Routledge.Google Scholar logo with link to Google Scholar
Dijkstra, T., Moscoso del Prado Martín, F., Schulpen, B., Schreuder, R., & Baayen, R. H. (2005). A roommate in cream: Morphological family size effects on interlingual homograph recognition. Language and Cognitive Processes, 201, 7 – 41. Google Scholar logo with link to Google Scholar
Ford, M. A., Davis, M. H., & Marslen-Wilson, W. D. (2010). Derivational morphology and base morpheme frequency. Journal of Memory and Language, 631, 117 – 130. Google Scholar logo with link to Google Scholar
Frauenfelder, U. H., & Schreuder, R. (1992). Constraining psycholinguistic models of morphological processing and representation: The role of productivity (pp. 165–183). Springer Netherlands.Google Scholar logo with link to Google Scholar
Friedman, J., Hastie, T., & Tibshirani, R. (2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33(1), 1 – 22. Google Scholar logo with link to Google Scholar
Friedman, J., Hastie, T., Tibshirani, R., Simon, N., Narasimhan, B., & Qian, J. (2018). Package “glmnet”, Version 2.0–13.Google Scholar logo with link to Google Scholar
Hassan, A. (2006). Morfologi. PTS Professional Publishing.Google Scholar logo with link to Google Scholar
Heitmeier, M., Chuang, Y.-Y., Axen, S. D., & Baayen, R. H. (2023). Frequency effects in linear discriminative learning. arXiv preprint arXiv:2306.11044. Google Scholar logo with link to Google Scholar
Jared, D., Jouravlev, O., & Joanisse, M. F. (2017). The effect of semantic transparency on the processing of morphologically derived words: Evidence from decision latencies and event-related potentials. Journal of Experimental Psychology: Learning, Memory, & Cognition, 431, 422 – 450. Google Scholar logo with link to Google Scholar
Järvikivi, J., Bertram, R., & Niemi, J. (2006). Affixal salience and the processing of derivational morphology: The role of suffix allomorphy. Language and Cognitive Processes, 21(4), 394 – 431. Google Scholar logo with link to Google Scholar
Kauschke, C., Stenneken, P. (2008). Differences in Noun and Verb Processing in Lexical Decision Cannot be Attributed to Word Form and Morphological Complexity Alone. J Psycholinguist Res 371, 443 – 452. Google Scholar logo with link to Google Scholar
Kuperman, V., Bertram, R., & Baayen, R. H. (2010). Processing trade-offs in the reading of Dutch derived words. Journal of Memory and Language, 621, 83 – 97. Google Scholar logo with link to Google Scholar
Laudanna, A., & Burani, C. (1995). Distributional properties of derivational affixes: Implications for processing. In L. B. Feldman (Ed.), Morphological aspects of language processing (pp. 345 – 364). Lawrence Erlbaum Associates, Inc.Google Scholar logo with link to Google Scholar
Laudanna, A., Burani, C., & Cermele, A. (1994). Prefixes as processing units. Language and Cognitive Processes, 9(3), 295 – 316. Google Scholar logo with link to Google Scholar
Li, Z. & Wood, S. N. (2019). Faster model matrix crossproducts for large generalized linear models with discretized covariates. Statistics and Computing, 301, 19 – 25. Google Scholar logo with link to Google Scholar
Lõo, K., Järvikivi, J., & Baayen, R. H. (2018). Whole-word frequency and inflectional paradigm size facilitate Estonian case-inflected noun processing. Cognition, 1751, 20 – 25. Google Scholar logo with link to Google Scholar
Mailhot, H., Wilson, M. A., Macoir, J., Deacon, S. H., & Sánchez-Gutiérrez, C. H. (2020). MorphoLex-FR: A derivational morphological database for 38,840 French words. Behavior Research Methods, 521, 1008 – 1025. Google Scholar logo with link to Google Scholar
Marelli, M., & Baroni, M. (2015). Affixation in semantic space: Modeling morpheme meanings with compositional distributional semantics. Psychological Review, 122(3), 485 – 515. Google Scholar logo with link to Google Scholar
Marelli, M., Traficante, D., & Burani, C. (2020). Reading morphologically complex words: Experimental evidence and learning models. In V. Pirelli, I. Plag, & U. Dressler (Eds.), Word knowledge and word usage: A cross-disciplinary guide to the mental lexicon (pp. 553 – 592). De Gruyter Mouton. Google Scholar logo with link to Google Scholar
Maziyah Mohamed, M., Yap, M. J., Chee, Q. W., Jared, D. (2023). Malay Lexicon Project 2: Morphology in Malay word recognition. Memory and Cognition, 511, 647 – 665. Google Scholar logo with link to Google Scholar
Moscoso del Prado Martín, F., Bertram, R., Häikiö, T., Schreuder, R., & Baayen, R. H. (2004). Morphological family size in a morphologically rich language: The case of Finnish compared with Dutch and Hebrew. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(6), 1271 – 1278. Google Scholar logo with link to Google Scholar
Moscoso del Prado Martin, F., Deutsch, A., Frost, R., Schreuder, R., Jong, N. H. de, and Baayen, R. H. (2005). Changing places: A cross-language perspective on frequency and family size in Dutch and Hebrew. Journal of Memory and Language, 531, 496–512. Google Scholar logo with link to Google Scholar
Plaut, D. C., & Gonnerman, L. M. (2000). Are non-semantic morphological effects incompatible with a distributed connectionist approach to lexical processing? Language and Cognitive Processes, 15(4–5), 445 – 485. Google Scholar logo with link to Google Scholar
R Core Team (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL [URL]
Rastle, K., & Davis, M. H. (2008). Morphological decomposition based on the analysis of orthography. Language and Cognitive Processes, 23(7–8), 942 – 971. Google Scholar logo with link to Google Scholar
Rastle, K., Davis, M. H., & New, B. (2004). The broth in my brother’s brothel: Morpho-orthographic segmentation in visual word recognition. Psychonomic Bulletin & Review, 11(6), 1090–1098. Google Scholar logo with link to Google Scholar
Rueckl, J. G., & Seidenberg, M. S. (2009). Computational modeling and the neural bases of reading and reading disorders. In K. Pugh & P. McCardle (Eds.), How children learn to read: Current issues and new directions in the integration of cognition, neurobiology and genetics of reading and dyslexia research and practice (pp. 101 – 133). Psychology Press.Google Scholar logo with link to Google Scholar
Rueckl, J. G., & Raveh, M. (1999). The influence of morphological regularities on the dynamics of a connectionist network. Brain and Language, 68(1–2), 110–117. Google Scholar logo with link to Google Scholar
Sánchez-Gutiérrez, C. H., Mailhot, H., & Deacon, S. H. (2018). MorphoLex: A derivational morphological database for 70,000 English words. Behavior Research Methods, 50(4), 1568 – 1580. Google Scholar logo with link to Google Scholar
Schreuder, R., & Baayen, R. H. (1995). Modeling morphological processing. In L. B. Feldman (Ed.), Morphological aspects of language processing (pp. 131 – 154). Lawrence Erlbaum Associates, Inc.Google Scholar logo with link to Google Scholar
(1997). How complex simplex words can be. Journal of Memory and Language, 37(1), 118 – 139. Google Scholar logo with link to Google Scholar
Taft, M. (2006). A localist-cum-distributed (LCD) framework for lexical processing. In S. Andrews (Ed.), From inkmarks to ideas: Current issues in lexical processing (pp. 76 – 94). Hove, UK: Psychology Press.Google Scholar logo with link to Google Scholar
(2023). Localist Lexical Representation of Polymorphemic Words: The AUSTRAL Model. In Linguistic Morphology in the Mind and Brain (pp. 152 – 166). Routledge. Google Scholar logo with link to Google Scholar
Taft, M., & Ardasinski, S. (2006). Obligatory decomposition in reading prefixed words. The Mental Lexicon, 1(2), 183 – 199. Google Scholar logo with link to Google Scholar
Taft, M., & Forster, K. I. (1975). Lexical storage and retrieval of prefixed words. Journal of Verbal Learning & Verbal Behavior, 14(6), 638 – 647. Google Scholar logo with link to Google Scholar
(1976). Lexical storage and retrieval of polymorphemic and polysyllabic words. Journal of Verbal Learning & Verbal Behavior, 15(6), 607 – 620. Google Scholar logo with link to Google Scholar
Tomaschek, F., Hendrix, P., & Baayen, R. H. (2018). Strategies for managing collinearity in multivariate linguistic data. Journal of Phonetics, 711, 249 – 267. Google Scholar logo with link to Google Scholar
Vannest, J., Bertram, R., Järvikivi, J., & Niemi, J. (2002). Counterintuitive cross-linguistic differences: More morphological computation in English than in Finnish. Journal of Psycholinguistic Research, 31(2), 83 – 106. Google Scholar logo with link to Google Scholar
van Rij, J., Wieling, M., Baayen, R., van Rijn, H. (2020). “itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs.” R package version 2.4.Google Scholar logo with link to Google Scholar
Wood, S. (2017). Generalized Additive Models: An Introduction with R (2nd ed.). Chapman and Hall/CRC. Google Scholar logo with link to Google Scholar
Wood, S.N., Li, Z., Shaddick, G. & Augustin N.H. (2017). Generalized additive models for gigadata: Modeling the U.K. black smoke network daily data. Journal of the American Statistical Association, 112(519),1199 – 1210. Google Scholar logo with link to Google Scholar
Yap, M. J., Rickard Liow, S. J., Jalil, S., & Faizal, S. S. (2010). The Malay Lexicon Project: A database of lexical statistics for 9,592 words. Behavior Research Methods, 42(4), 992 – 1003. Google Scholar logo with link to Google Scholar
Cited by (2)

Cited by two other publications

Maziyah Mohamed, Mirrah & Debra Jared
2025. Malay Lexicon Project 3: The impact of orthographic–semantic consistency on lexical decision latencies. Quarterly Journal of Experimental Psychology 78:1  pp. 22 ff. DOI logo
Yap, Melvin J. & Mirrah Maziyah Mohamed
2025. Malay Lexicon Project. In Reference Module in Social Sciences, DOI logo

This list is based on CrossRef data as of 27 november 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

Mobile Menu Logo with link to supplementary files background Layer 1 prag Twitter_Logo_Blue