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The guides and the function reference pages cite published work throughout, and this page carries the full entries so that every citation on the site resolves. Each guide also lists the works it cites at its own foot, and this page gathers those lists together with the works cited only in the function documentation and in the design configurations that ship with the package. Every entry carries a DOI wherever the work has one, and any work cited on both sites reads the same here as on the Python twin’s reference page. The lexical corpora that lexsync reads are attributed separately, in corpora/ATTRIBUTION.md and in the corpus registry, since their licences travel with the derived data rather than with the software.

Andrews, S. (1989). Frequency and neighborhood effects on lexical access: Activation or search? Journal of Experimental Psychology: Learning, Memory, and Cognition, 15(5), 802–814. https://doi.org/10.1037/0278-7393.15.5.802

Armstrong, B. C., Watson, C. E., & Plaut, D. C. (2012). SOS! An algorithm and software for the stochastic optimization of stimuli. Behavior Research Methods, 44(3), 675–705. https://doi.org/10.3758/s13428-011-0182-9

Austin, P. C. (2009). Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Statistics in Medicine, 28(25), 3083–3107. https://doi.org/10.1002/sim.3697

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. https://doi.org/10.1016/j.jml.2007.12.005

Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68(3), 255–278. https://doi.org/10.1016/j.jml.2012.11.001

Bochynska, A., Keeble, L., Halfacre, C., Casillas, J. V., Champagne, I.-A., Chen, K., Röthlisberger, M., Buchanan, E. M., & Roettger, T. B. (2023). Reproducible research practices and transparency across linguistics. Glossa Psycholinguistics, 2(1). https://doi.org/10.5070/G6011239

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. https://doi.org/10.1016/S0022-5371(73)80014-3

Coltheart, M., Davelaar, E., Jonasson, J. T., & Besner, D. (1977). Access to the internal lexicon. In S. Dornic (Ed.), Attention and Performance VI (pp. 535–555). Erlbaum.

Forster, K. I. (2000). The potential for experimenter bias effects in word recognition experiments. Memory & Cognition, 28(7), 1109–1115. https://doi.org/10.3758/BF03211812

González Alonso, J., Bernabeu, P., Silva, G., DeLuca, V., Poch, C., Ivanova, I., & Rothman, J. (2025). Starting from the very beginning: Unraveling third language (L3) development with longitudinal data from artificial language learning and EEG. International Journal of Multilingualism, 22(1), 119–142. https://doi.org/10.1080/14790718.2024.2415993

Gu, X. S., & Rosenbaum, P. R. (1993). Comparison of multivariate matching methods: Structures, distances, and algorithms. Journal of Computational and Graphical Statistics, 2(4), 405–420. https://doi.org/10.1080/10618600.1993.10474623

Hansen, B. B., & Klopfer, S. O. (2006). Optimal full matching and related designs via network flows. Journal of Computational and Graphical Statistics, 15(3), 609–627. https://doi.org/10.1198/106186006X137047

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

Kuperman, V. (2015). Virtual experiments in megastudies: A case study of language and emotion. Quarterly Journal of Experimental Psychology, 68(8), 1693–1710. https://doi.org/10.1080/17470218.2014.989865

Lakens, D. (2017). Equivalence tests: A practical primer for t tests, correlations, and meta-analyses. Social Psychological and Personality Science, 8(4), 355–362. https://doi.org/10.1177/1948550617697177

Liben-Nowell, D., Strand, J., Sharp, A., Wexler, T., & Woods, K. (2019). The danger of testing by selecting controlled subsets, with applications to spoken-word recognition. Journal of Cognition, 2(1), Article 2. https://doi.org/10.5334/joc.51

Mathôt, S., Schreij, D., & Theeuwes, J. (2012). OpenSesame: An open-source, graphical experiment builder for the social sciences. Behavior Research Methods, 44(2), 314–324. https://doi.org/10.3758/s13428-011-0168-7

Matuschek, H., Kliegl, R., Vasishth, S., Baayen, H., & Bates, D. (2017). Balancing Type I error and power in linear mixed models. Journal of Memory and Language, 94, 305–315. https://doi.org/10.1016/j.jml.2017.01.001

Peirce, J., Gray, J. R., Simpson, S., MacAskill, M., Höchenberger, R., Sogo, H., Kastman, E., & Lindeløv, J. K. (2019). PsychoPy2: Experiments in behavior made easy. Behavior Research Methods, 51(1), 195–203. https://doi.org/10.3758/s13428-018-01193-y

Roettger, T. B. (2019). Researcher degrees of freedom in phonetic research. Laboratory Phonology, 10(1), Article 1. https://doi.org/10.5334/labphon.147

Rubin, D. B. (1980). Bias reduction using Mahalanobis-metric matching. Biometrics, 36(2), 293–298. https://doi.org/10.2307/2529981

Sassenhagen, J., & Alday, P. M. (2016). A common misapplication of statistical inference: Nuisance control with null-hypothesis significance tests. Brain and Language, 162, 42–45. https://doi.org/10.1016/j.bandl.2016.08.001

Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359–1366. https://doi.org/10.1177/0956797611417632

Stuart, E. A. (2010). Matching methods for causal inference: A review and a look forward. Statistical Science, 25(1), 1–21. https://doi.org/10.1214/09-STS313

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

Wilkinson, M. D., Dumontier, M., Aalbersberg, IJ. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, Article 160018. https://doi.org/10.1038/sdata.2016.18

Yarkoni, T. (2022). The generalizability crisis. Behavioral and Brain Sciences, 45, Article e1. https://doi.org/10.1017/S0140525X20001685

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. https://doi.org/10.3758/PBR.15.5.971