Tools

Corpora

Brazilian Portuguese Lexicon - LexPorBR - Brazilian Portuguese

Linguateca - European/Brazilian Portuguese

Corpus do Português - Brigham Young University (BYU) - European Portuguese

Lexique - French

Les Atlas Sémantiques - English, French, and Spanish

ClearPOND - Dutch, English, French, German, and Spanish

CELEX - Cyrillic, Dutch, English, and German

Worldlex - 66 languages

SUBTLEX - Subtitle Word Frequencies - Chinese, Dutch, Englis (US and UK), German, Greek, Polish, Spanish

MRC Psycholinguistic Database - English

British National Corpus (BNC) - Brigham Young University (BYU) - English

WordNet - English

ARC Nonword Database - pseudoword corpus - English

Google Books Ngram Viewer - Ngram corpus

Softwares and Packages

R - statistical software

languageR - R package

vwr - R package

zipfR - R package

lme4 - R package

psych - R package

LEXOP - psycholinguistic statistics - French

N-Watch - psycholinguistic statistics - English

BuscaPalabras - psycholinguistic statistics - Spanish

E-Hitz - psycholinguistic statistics - Basque

Sillabarium - psycholinguistic statistics - Basque and Spanish

Wuggy - pseudoword generator - Basque, Dutch, English, French, German, Serbian, Spanish, and Vietnamese

WordGen - corpus, psycholinguistic statistics, and pseudoword generator - Dutch, English, French, and German

Mix - word mix pseudorandomization

Match - word match combination

DMDX - programa psycholinguistic software

PsychoPy - psycholinguistic software

E-Prime v2.0 - psycholinguistic software

Presentation - psycholinguistic software

Science XL - psycholinguistic application

Literature

Corpora

link Estivalet, G. L., & Meunier, F. E. (2015). The Brazilian Portuguese Lexicon: An Instrument for Psycholinguistic Reserach. PLOS ONE, 10(12), e0144016. doi: 10.1371/journal.pone.0144016.

link Gimenes, M., & New, B. (2015). Worldlex: Twitter and blog word frequencies for 66 languages. Behavior Research Methods. doi:10.3758/s13428-015-0621-0.

link Van Heuven, W. J. B., Mandera, P., Keuleers, E., & Brysbaert, M. (2014). SUBTLEX-UK: A new and improved word frequency database for British English. The Quarterly Journal of Experimental Psychology, 67(6), 1176–1190. doi:10.1080/17470218.2013.850521.

link Tang, K. (2012). A 61 Million Word Corpus of Brazilian Portuguese Film Subtitles as a Resource for Linguistic Research. UCL Working Papers in Linguistics, 24, 208–214.

link Marian, V., Bartolotti, J., Chabal, S., & Shook, A. (2012). CLEARPOND: Cross-Linguistic Easy-Access Resource for Phonological and Orthographic Neighborhood Densities. PLoS ONE, 7(8), e43230. doi: 10.1371/journal.pone.0043230.

link Keuleers, E., Lacey, P., Rastle, K., & Brysbaert, M. (2012). The British Lexicon Project: Lexical decision data for 28,730 monosyllabic and disyllabic English words. Behavior Research Methods, 44(1), 287-304. doi: 10.3758/s13428-011-0118-4.

link Keuleers, E., Brysbaert, M., & New, B. (2010). SUBTLEX-NL: A new measure for Dutch word frequency based on film subtitles. Behavior Research Methods, 42(3), 643–650. doi:10.3758/BRM.42.3.643.

link Ferrand, L., New, B., Brysbaert, M., Keuleers, E., Bonin, P., Méot, A., Augustinova, M., Pallier, C. (2010). The French Lexicon Project: Lexical decision data for 38,840 French words and 38,840 pseudowords. Behavior Research Methods, 42(2), 488-496. doi: 10.3758/brm.42.2.488.

link Keuleers, E., Diependaele, K., & Brysbaert, M. (2010). Practice effects in large-scale visual word recognition studies: A lexical decision study on 14,000 Dutch mono- and disyllabic words and nonwords. Frontiers in Psychology, 1. doi: 10.3389/fpsyg.2010.00174.

link Brysbaert, M., & New, B. (2009). Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior Research Methods, 41(4), 977–990. doi:10.3758/BRM.41.4.977.

link Balota, D. A., Yap, M. J., Hutchison, K. A., Cortese, M. J., Kessler, B., Loftis, B., Neely, J. H., Nelson, D. L., Simpson, G. B., Treiman, R. (2007). The English Lexicon Project. Behavior Research Methods, 39(3), 445-459. doi: 10.3758/bf03193014.

link New, B., Ferrand, L., Pallier, C., & Brysbaert, M. (2006). Reexamining the word length effect in visual word recognition: New evidence from the English Lexicon Project. Psychonomic Bulletin & Review, 13(1), 45-52. doi: 10.3758/bf03193811.

link New, B., Pallier, C., Brysbaert, M., & Ferrand, L. (2004). Lexique 2 : A new French lexical database. Behavior Research Methods, Instruments, & Computers, 36(3), 516-524. doi: 10.3758/bf03195598.

link Matos, R., Ferrand, L., Pallier, C., & New, B. (2001). Une base de données lexicales du français contemporain sur internet : LEXIQUE™//A lexical database for contemporary french : LEXIQUE™. L'Année Psychologique, 447-462. doi: 10.3406/psy.2001.1341.

link Maria das Graças Volpe Nunes, Fabiano M. Costa Vieira, Cláudia Zavaglia, Cássia R. C. Sossolote & Josélia Hernandez. A construção de um léxico para o português do Brasil: lições aprendidas e perspectivas. In Anais do II Encontro para o processamento de português escrito e Falado (Curitiba, PR, 21-22 de Outubro de 1996), Curitiba: CEFET-PR, pp. 61-70.

link Maria das Graças Volpe Nunes, Claudete M. Ghiraldelo, Gisele Montilha, Marcelo A. S. Turine, Maria Cristina F. de Oliveira, Ricardo Hasegawa, Ronaldo T. Martins & Osvaldo N. Oliveira Jr. Desenvolvimento de um sistema de revisão gramatical automática para o português do Brasil. In Anais do II Encontro para o processamento de português escrito e Falado (Curitiba, PR, 21-22 de Outubro de 1996), Curitiba: CEFET-PR, pp. 71-80.

Psycholinguistics

link Dufau, S., Duñabeitia, J. A., Moret-Tatay, C., McGonigal, A., Peeters, D., Alario, F.-X., … Grainger, J. (2011). Smart Phone, Smart Science: How the Use of Smartphones Can Revolutionize Research in Cognitive Science. PLoS ONE, 6(9), e24974. doi:10.1371/journal.pone.0024974.

link Duñabeitia, J., Cholin, J., Corral, J., Perea, M., & Carreiras, M. (2010). SYLLABARIUM: An online application for deriving complete statistics for Basque and Spanish orthographic syllables. Behavior Research Methods, 42(1), 118–125. doi: 10.3758/BRM.42.1.118.

link Yarkoni, T., Balota, D., & Yap, M. (2008). Moving beyond Coltheart’s N: A new measure of orthographic similarity. Psychonomic Bulletin & Review, 15(5), 971-979. doi: 10.3758/pbr.15.5.971.

link Peirce, J. W. (2007). PsychoPy—Psychophysics software in Python. Journal of Neuroscience Methods, 162(1–2), 8–13. doi: 10.1016/j.jneumeth.2006.11.017.

link Perea, M., Urkia, M., Davis, C., Agirre, A., Laseka, E., & Carreiras, M. (2006). E-Hitz: A word frequency list and a program for deriving psycholinguistic statistics in an agglutinative language (Basque). Behavior Research Methods, 38(4), 610–615. doi: 10.3758/BF03193893.

link van Casteren, M., Davis M. (2007). Match: A program to assist in matching the conditions of factorial experiments. Behavior Research Methods, 39(4), 973–978. doi: 10.3758/BF03192992.

link van Casteren, M., Davis, M. (2006). Mix, a program for pseudorandomization. Behavior Research Methods, 38(4), 584–589. doi: 10.3758/BF03193889.

link Davis, C. J., & Perea, M. (2005). BuscaPalabras: A program for deriving orthographic and phonological neighborhood statistics and other psycholinguistic indices in Spanish. Behavior Research Methods, 37(4), 665-671. doi: 10.3758/bf03192738.

link Davis, C. J. (2005). N-Watch: A program for deriving neighborhood size and other psycholinguistic statistics. Behavior Research Methods, 37(1), 65-70. doi: 10.3758/bf03206399.

link Forster, K., & Forster, J. (2003). DMDX: A Windows display program with millisecond accuracy. Behavior Research Methods, Instruments, & Computers, 35(1), 116-124. doi: 10.3758/BF03195503.

link Peereman, R., & Content, A. (1999). LEXOP: A lexical database providing orthography-phonology statistics for French monosyllabic words. Behavior Research Methods, Instruments, & Computers, 31(2), 376-379. doi: 10.3758/bf03207735.

link Burgess, C., & Livesay, K. (1998). The effect of corpus size in predicting reaction time in a basic word recognition task: Moving on from Kučera and Francis. Behavior Research Methods, Instruments, & Computers, 30(2), 272–277. doi:10.3758/BF03200655.

link Cutler, A. (1981). Making up materials is a confounded nuisance, or: Will we able to run any psycholinguistic experiments at all in 1990? Cognition, 10(1–3), 65–70. doi:10.1016/0010-0277(81)90026-3.

link Coltheart, M., Davelaar, E., Jonasson, J. T., & Besner, D. (1977). Access to the internal lexicon. In S. Dornic (Ed.). Attention and Performance VI, p.535-555). Hillsdale, NJ: Lawrence Erlbaum Associates.

Statistics

link Keuleers, E. (2013). R Package 'vwr': Useful functions for visual word recognition research.

link Knoblauch, K., & Maloney, L. T. (2012). Modeling Psychophysical Data in R. New York, USA: Springer.

link Baayen, R. H., & Milin, P. (2010). Analyzing Reaction Times. International Journal of Psychological Research, 3(2), 12-28.

link Baayen, R. H. (2013). R Package 'languageR': Data sets and functions with 'Analyzing Linguistic Data: A practical introduction to statistics'.

link Baayen, R. H. (2008). Analyzing Linguistic Data: A Practical Introduction to Statistics. Cambridge: Cambridge University Press.

link Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390-412. doi: 10.1016/j.jml.2007.12.005.

link Whelan, R. (2008). Effective analysis of reaction time data. The Psychological Record, 58(3), 475-482.

link Bates, D. M. (2005). Fitting linear mixed models. R News, 5(1), 27-30.

link Raaijmakers, J. G. W., Schrijnemakers, J. M. C., & Gremmen, F. (1999). How to Deal with “The Language-as-Fixed-Effect Fallacy”: Common Misconceptions and Alternative Solutions. Journal of Memory and Language, 41(3), 416-426. doi: 10.1006/jmla.1999.2650.

link Ratcliff, R. (1993). Methods for dealing with reaction time outliers. Psychological Bulletin, 114(3), 510-532. doi: 10.1037/0033-2909.114.3.510.

link Forster, K. I., & Dickinson, R. G. (1976). More on the language-as-fixed-effect fallacy: Monte Carlo estimates of error rates for F1, F2, F′, and min F′. Journal of Verbal Learning and Verbal Behavior, 15(2), 135-142. doi: 10.1016/0022-5371(76)90014-1.

link Clark, H. H. (1973). The language-as-fixed-effect fallacy: A critique of language statistics in psychological research. Journal of Verbal Learning and Verbal Behavior, 12(4), 335-359. doi: 10.1016/S0022-5371(73)80014-3.

link Levenshtein, V. I. (1966). Binary Codes Capable of Correcting Deletions, Insertions, and reversals. Soviet Physics Doklady, 10(8), 707–710.

link Hamming, R. W. (1950). Error Detecting and Error Correcting Codes. The Bell System Technical Journal, XXIX(2).

Pseudowords

link Mota, M. B., & Resende, N. (2013). Metodologia da pesquisa em psicolinguística: desenvolvimento de uma ferramenta para a geração automática de pseudoverbos. Letras de Hoje, 48(1), 100-107.

link Keuleers, E., & Brysbaert, M. (2010). Wuggy: A multilingual pseudoword generator. Behavior Research Methods, 42(3), 627-633. doi: 10.3758/BRM.42.3.627.

link Duyck, W., Desmet, T., Verbeke, L. C., & Brysbaert, M. (2004). WordGen: A tool for word selection and nonword generation in Dutch, English, German, and French. Behavior Research Methods, Instruments, & Computers, 36(3), 488–499. doi:10.3758/BF03195595.

link Rastle, K., Harrington, J., & Coltheart, M. (2002). 358,534 nonwords: The ARC Nonword Database. Quarterly Journal of Experimental Psychology, 55A, 1339-1362. doi:10.1080/02724980244000099.