Many domains of inquiry in psychology are concerned with rich and complex phenomena. At the same time, the field of psychology is grappling with how to improve research practices to address concerns with the scientific enterprise. In this Perspective, we argue that both of these challenges can be addressed by adopting a principle of methodological variety. According to this principle, developing a variety of methodological tools should be regarded as a scientific goal in itself, one that is critical for advancing scientific theory. To illustrate, we show how the study of language and communication requires varied methodologies, and that theory development proceeds, in part, by integrating disparate tools and designs. We argue that the importance of methodological variation and innovation runs deep, travelling alongside theory development to the core of the scientific enterprise. Finally, we highlight ongoing research agendas that might help to specify, quantify and model methodological variety and its implications.
This is a preview of subscription content, access via your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 per month
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$59.00 per year
only $4.92 per issue
Rent or buy this article
Get just this article for as long as you need it
Prices may be subject to local taxes which are calculated during checkout
Hacking, I. Representing and Intervening: Introductory Topics in The Philosophy of Natural Science (Cambridge Univ. Press, 1983).
Mayo, D. G. in PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association Vol. 1994, 270–279 (Cambridge Univ. Press, 1994).
Ackermann, R. The new experimentalism. Brit. J. Philos. Sci. 40, 185–190 (1989).
Simons, M. & Vagelli, M. Were experiments ever neglected? Ian Hacking and the history of philosophy of experiment. Phil. Inq. 9, 167–188 (2021).
Nosek, B. A. et al. Promoting an open research culture. Science 348, 1422–1425 (2015).
Richardson, D. C., Dale, R. & Tomlinson, J. M. Conversation, gaze coordination, and beliefs about visual context. Cogn. Sci. 33, 1468–1482 (2009).
Laidlaw, K. E., Foulsham, T., Kuhn, G. & Kingstone, A. Potential social interactions are important to social attention. Proc. Natl Acad. Sci. USA 108, 5548–5553 (2011).
Richardson, D. C. et al. Joint perception: gaze and social context. Front. Hum. Neurosci. 6, 194 (2012).
Risko, E. F., Richardson, D. C. & Kingstone, A. Breaking the fourth wall of cognitive science: real-world social attention and the dual function of gaze. Curr. Dir. Psychol. Sci. 25, 70–74 (2016).
Levin, I. P., Schneider, S. L. & Gaeth, G. J. All frames are not created equal: a typology and critical analysis of framing effects. Organ. Behav. Hum. Decis. Process. 76, 149–188 (1998).
Pothos, E. M. & Busemeyer, J. R. A quantum probability explanation for violations of ‘rational’ decision theory. Proc. R. Soc. B 276, 2171–2178 (2009).
Pärnamets, P. et al. Biasing moral decisions by exploiting the dynamics of eye gaze. Proc. Natl Acad. Sci. USA 112, 4170–4175 (2015).
Vinson, D. W., Dale, R. & Jones, M. N. Decision contamination in the wild: sequential dependencies in online review ratings. Behav. Res. Methods 51, 1477–1484 (2019).
Longino, H. E. Gender, politics, and the theoretical virtues. Synthese 104, 383–397 (1995).
Hansson, S. O. in Stanford Encyclopedia of Philosophy (ed. Zalta, E. N.) https://plato.stanford.edu/archives/fall2021/entries/pseudo-science/ (Stanford Univ., 2015).
Dupré, J. The Disorder of Things: Metaphysical Foundations of the Disunity of Science (Harvard Univ. Press, 1993).
Cartwright, N. The Dappled World: A Study of the Boundaries of Science (Cambridge Univ. Press, 1999).
McCauley, R. N. & Bechtel, W. Explanatory pluralism and heuristic identity theory. Theory Psychol. 11, 736–760 (2001).
Mitchell, S. D. Integrative pluralism. Biol. Phil. 17, 55–70 (2002).
Abrahamsen, A. & Bechtel, W. in Contemporary Debates in Cognitive Science (ed. Stainton, R.) 159–187 (Blackwell, 2006).
Kellert, S. H., Longino, H. E. & Waters, C. K. Scientific Pluralism (Univ. Minnesota Press, 2006).
Dale, R., Dietrich, E. & Chemero, A. Explanatory pluralism in cognitive science. Cogn. Sci. 33, 739–742 (2009).
Weisberg, M. & Muldoon, R. Epistemic landscapes and the division of cognitive labor. Phil. Sci. 76, 225–252 (2009).
Zollman, K. J. S. The epistemic benefit of transient diversity. Erkenntnis 72, 17–35 (2010).
Horst, S. Beyond reduction: from naturalism to cognitive pluralism. Mind Matter 12, 197–244 (2014).
Open Science Collaboration. Estimating the reproducibility of psychological science. Science 349, 943 (2015).
Lin, H., Werner, K. M. & Inzlicht, M. Promises and perils of experimentation: the mutual-internal-validity problem. Perspect. Psychol. Sci. 16, 854–863 (2021).
van Rooij, I. & Baggio, G. Theory before the test: how to build high-verisimilitude explanatory theories in psychological science. Perspect. Psychol. Sci. 16, 682–697 (2021).
MacLeod, C. M. The Stroop task: the gold standard of attentional measures. J. Exp. Psychol. Gen. 121, 12–14 (1992).
Eriksen, C. W. The flankers task and response competition: a useful tool for investigating a variety of cognitive problems. Vis. Cogn. 2, 101–118 (1995).
Dickter, C. L. & Bartholow, B. D. Ingroup categorization and response conflict: interactive effects of target race, flanker compatibility, and infrequency on N2 amplitude. Psychophysiology 47, 596–601 (2010).
Parris, B. A., Hasshim, N., Wadsley, M., Augustinova, M. & Ferrand, L. The loci of Stroop effects: a critical review of methods and evidence for levels of processing contributing to color-word Stroop effects and the implications for the loci of attentional selection. Psychol. Res. 86, 1029–1053 (2022).
Barzykowski, K., Wereszczyski, M., Hajdas, S. & Radel, R. Cognitive inhibition behavioral tasks in online and laboratory settings: data from Stroop, SART and Eriksen Flanker tasks. Data Brief. 43, 108398 (2022).
Gobel, M. S., Kim, H. S. & Richardson, D. C. The dual function of social gaze. Cognition 136, 359–364 (2015).
Gallup, A. C., Chong, A. & Couzin, I. D. The directional flow of visual information transfer between pedestrians. Biol. Lett. 8, 520–522 (2012).
Lick, D. J. & Johnson, K. L. Straight until proven gay: a systematic bias toward straight categorizations in sexual orientation judgments. J. Pers. Soc. Psychol. 110, 801 (2016).
Alt, N. P., Lick, D. J. & Johnson, K. L. The straight categorization bias: a motivated and altruistic reasoning account. J. Pers. Soc. Psychol. https://doi.org/10.1037/pspi0000232 (2020).
Popper, K. Conjectures and Refutations: The Growth of Scientific Knowledge (Routledge, 2002).
Heit, E. & Hahn, U. Diversity-based reasoning in children. Cogn. Psychol. 43, 243–273 (2001).
Heit, E., Hahn, U. & Feeney, A. in Categorization Inside and Outside the Laboratory: Essays in Honor of Douglas L. Medin 87–99 (American Psychological Association, 2005).
MacWhinney, B. in The Handbook of Linguistics 2nd edn (eds. Aronoff, M. & Rees-Miller, J.) 397–413 (Wiley, 2017).
Stivers, T. et al. Universals and cultural variation in turn-taking in conversation. Proc. Natl Acad. Sci. USA 106, 10587–10592 (2009).
Louwerse, M. M., Dale, R., Bard, E. G. & Jeuniaux, P. Behavior matching in multimodal communication is synchronized. Cogn. Sci. 36, 1404–1426 (2012).
Fusaroli, R., Bjørndahl, J. S., Roepstorff, A. & Tylén, K. A heart for interaction: shared physiological dynamics and behavioral coordination in a collective, creative construction task. J. Exp. Psychol. Hum. Percept. Perform. 42, 1297 (2016).
Rasenberg, M., Özyürek, A. & Dingemanse, M. Alignment in multimodal interaction: an integrative framework. Cogn. Sci. 44, e12911 (2020).
Dunn, M., Greenhill, S. J., Levinson, S. C. & Gray, R. D. Evolved structure of language shows lineage-specific trends in word-order universals. Nature 473, 79–82 (2011).
Hua, X., Greenhill, S. J., Cardillo, M., Schneemann, H. & Bromham, L. The ecological drivers of variation in global language diversity. Nat. Commun. 10, 1–10 (2019).
Christiansen, M. H. & Chater, N. The now-or-never bottleneck: a fundamental constraint on language. Behav. Brain Sci. 39, e62 (2016).
Fitch, W. T., De Boer, B., Mathur, N. & Ghazanfar, A. A. Monkey vocal tracts are speech-ready. Sci. Adv. 2, e1600723 (2016).
Hauser, M. D., Chomsky, N. & Fitch, W. T. The faculty of language: what is it, who has it, and how did it evolve? Science 298, 1569–1579 (2002).
Cowley, S. J. Distributed Language (John Benjamins, 2011).
Samuels, R. Nativism in cognitive science. Mind Lang. 17, 233–265 (2002).
Behme, C. & Deacon, S. H. Language learning in infancy: does the empirical evidence support a domain specific language acquisition device? Phil. Psychol. 21, 641–671 (2008).
Chomsky, N. 4. A Review Of BF Skinner’s Verbal Behavior (Harvard Univ. Press, 2013).
Vihman, M. M. Phonological Development: The Origins of Language in the Child (Blackwell, 1996).
Oller, D. K. The Emergence of the Speech Capacity (Psychology Press, 2000).
Clark, E. V. & Casillas, M. First Language Acquisition (Routledge, 2015).
Goldstein, M. H., King, A. P. & West, M. J. Social interaction shapes babbling: testing parallels between birdsong and speech. Proc. Natl Acad. Sci. USA 100, 8030–8035 (2003).
Warlaumont, A. S. Modeling the emergence of syllabic structure. J. Phonet. 53, 61–65 (2015).
VanDam, M. et al. HomeBank: An online repository of daylong child-centered audio recordings. Semin. Speech Lang. 37, 128–142 (2016).
Elmlinger, S. L., Schwade, J. A. & Goldstein, M. H. The ecology of prelinguistic vocal learning: parents simplify the structure of their speech in response to babbling. J. Child Lang. 46, 998–1011 (2019).
Roy, B. C., Frank, M. C., DeCamp, P., Miller, M. & Roy, D. Predicting the birth of a spoken word. Proc. Natl Acad. Sci. USA 112, 12663–12668 (2015).
McClelland, J. L. The place of modeling in cognitive science. Top. Cogn. Sci. 1, 11–38 (2009).
Smaldino, P. E. in Computational Social Psychology (eds Vallacher’, R., Read, S. J. & Nowak, A.) 311–331 (Routledge, 2017).
Guest, O. & Martin, A. E. How computational modeling can force theory building in psychological science. Perspect. Psychol. Sci. 16, 789–802 (2021).
Elman, J. L., Bates, E. A. & Johnson, M. H. Rethinking Innateness: A Connectionist Perspective on Development Vol. 10 (MIT Press, 1996).
Warlaumont, A. S., Westermann, G., Buder, E. H. & Oller, D. K. Prespeech motor learning in a neural network using reinforcement. Neural Netw. 38, 64–75 (2013).
Warlaumont, A. S. & Finnegan, M. K. Learning to produce syllabic speech sounds via reward-modulated neural plasticity. PLoS One 11, e0145096 (2016).
MacWhinney, B. & Snow, C. The child language data exchange system: an update. J. Child. Lang. 17, 457–472 (1990).
MacWhinney, B. The CHILDES Project: Tools for Analyzing Talk 3rd edn (Psychology Press, 2014).
Kachergis, G., Marchman, V. A. & Frank, M. C. Toward a “standard model” of early language learning. Curr. Dir. Psychol. Sci. 31, 20–27 (2022).
Lewis, J. D. & Elman, J. L. A connectionist investigation of linguistic arguments from the poverty of the stimulus: learning the unlearnable. In Proc. Annual Meeting of the Cognitive Science Society Vol. 23, 552–557 (eds. Moore, J. D. & Stenning, K.) (2001).
Regier, T. & Gahl, S. Learning the unlearnable: the role of missing evidence. Cognition 93, 147–155 (2004).
Reali, F. & Christiansen, M. H. Uncovering the richness of the stimulus: structure dependence and indirect statistical evidence. Cogn. Sci. 29, 1007–1028 (2005).
Foraker, S., Regier, T., Khetarpal, N., Perfors, A. & Tenenbaum, J. Indirect evidence and the poverty of the stimulus: the case of anaphoric one. Cognit. Sci. 33, 287–300 (2009).
Saffran, J. R., Aslin, R. N. & Newport, E. L. Statistical learning by 8-month-old infants. Science 274, 1926–1928 (1996).
McMurray, B. & Hollich, G. Core computational principles of language acquisition: can statistical learning do the job? Dev. Sci. 12, 365–368 (2009).
Frost, R., Armstrong, B. C., Siegelman, N. & Christiansen, M. H. Domain generality versus modality specificity: the paradox of statistical learning. Trends Cogn. Sci. 19, 117–125 (2015).
Isbilen, E. S., Frost, R. L. A., Monaghan, P. & Christiansen, M. H. Statistically based chunking of nonadjacent dependencies. J. Exp. Psychol. Gen. https://doi.org/10.1037/xge0001207 (2022).
Ruba, A. L., Pollak, S. D. & Saffran, J. R. Acquiring complex communicative systems: Statistical learning of language and emotion. Top. Cogn. Sci. https://doi.org/10.1111/tops.12612 (2022).
Abney, D. H., Warlaumont, A. S., Oller, D. K., Wallot, S. & Kello, C. T. Multiple coordination patterns in infant and adult vocalizations. Infancy 22, 514–539 (2017).
Mendoza, J. K. & Fausey, C. M. Everyday music in infancy. Dev. Sci. 24, e13122 (2019).
Ritwika, V. et al. Exploratory dynamics of vocal foraging during infant-caregiver communication. Sci. Rep. 10, 10469 (2020).
Mendoza, J. K. & Fausey, C. M. Quantifying everyday ecologies: principles for manual annotation of many hours of infants’ lives. Front. Psychol. 12, 710636 (2021).
Fernald, A., Zangl, R., Portillo, A. L. & Marchman, V. A. in Developmental Psycholinguistics: On-line Methods in Children’s Language Processing (eds. Sekerina, I. A., Fernández, E. M. & Clahsen, H.) Vol. 44, 97 (John Benjamins, 2008).
Weisleder, A. & Fernald, A. Talking to children matters: early language experience strengthens processing and builds vocabulary. Psychol. Sci. 24, 2143–2152 (2013).
Bergelson, E. & Aslin, R. N. Nature and origins of the lexicon in 6-mo-olds. Proc. Natl Acad. Sci. USA 114, 12916–12921 (2017).
Brennan, S. E., Galati, A. & Kuhlen, A. K. in Psychology of Learning and Motivation (ed. Ross, B. H.) Vol. 53, 301–344 (Elsevier, 2010).
Streeck, J., Goodwin, C. & LeBaron, C. Embodied Interaction: Language and Body in the Material World (Cambridge Univ. Press, 2011).
Goodwin, C. Co-operative Action (Cambridge Univ. Press, 2017).
Dale, R., Spivey, M. J. in Eye-Tracking In Interaction. Studies On The Role Of Eye Gaze In Dialogue (eds. Oben, B. and Brône, G.) 67–90 (John Benjamins, 2018).
Richardson, D. C. & Spivey, M. J. in Encyclopedia of Biomaterials and Biomedical Engineering 573–582 (CRC Press, 2004).
Tanenhaus, M. K., Spivey-Knowlton, M. J., Eberhard, K. M. & Sedivy, J. C. Integration of visual and linguistic information in spoken language comprehension. Science 268, 1632–1634 (1995).
Spivey, M. J., Tanenhaus, M. K., Eberhard, K. M. & Sedivy, J. C. Eye movements and spoken language comprehension: effects of visual context on syntactic ambiguity resolution. Cogn. Psychol. 45, 447–481 (2002).
Richardson, D. C., Dale, R. & Spivey, M. J. Eye movements in language and cognition. Methods Cogn. Linguist. 18, 323–344 (2007).
Ferreira, F. & Clifton, C. Jr The independence of syntactic processing. J. Mem. Lang. 25, 348–368 (1986).
Kamide, Y., Altmann, G. T. & Haywood, S. L. The time-course of prediction in incremental sentence processing: evidence from anticipatory eye movements. J. Mem. Lang. 49, 133–156 (2003).
Coco, M. I., Keller, F. & Malcolm, G. L. Anticipation in real‐world scenes: the role of visual context and visual memory. Cogn. Sci. 40, 1995–2024 (2016).
Coco, M. I. & Keller, F. Scan patterns predict sentence production in the cross‐modal processing of visual scenes. Cogn. Sci. 36, 1204–1223 (2012).
Kieslich, P. J., Henninger, F., Wulff, D. U., Haslbeck, J. M. & Schulte-Mecklenbeck, M. in A Handbook of Process Tracing Methods 111–130 (Routledge, 2019).
Spivey, M. J., Grosjean, M. & Knoblich, G. Continuous attraction toward phonological competitors. Proc. Natl Acad. Sci. USA 102, 10393–10398 (2005).
Freeman, J., Dale, R. & Farmer, T. Hand in motion reveals mind in motion. Front. Psychol. 2, 59 (2011).
Freeman, J. B. & Johnson, K. L. More than meets the eye: split-second social perception. Trends Cogn. Sci. 20, 362–374 (2016).
Goodale, B. M., Alt, N. P., Lick, D. J. & Johnson, K. L. Groups at a glance: perceivers infer social belonging in a group based on perceptual summaries of sex ratio. J. Exp. Psychol. Gen. 147, 1660–1676 (2018).
Sneller, B. & Roberts, G. Why some behaviors spread while others don’t: a laboratory simulation of dialect contact. Cognition 170, 298–311 (2018).
Atkinson, M., Mills, G. J. & Smith, K. Social group effects on the emergence of communicative conventions and language complexity. J. Lang. Evol. 4, 1–18 (2019).
Raviv, L., Meyer, A. & Lev‐Ari, S. The role of social network structure in the emergence of linguistic structure. Cogn. Sci. 44, e12876 (2020).
Lupyan, G. & Dale, R. Language structure is partly determined by social structure. PLoS One 5, e8559 (2010).
Lupyan, G. & Dale, R. Why are there different languages? The role of adaptation in linguistic diversity. Trends Cogn. Sci. 20, 649–660 (2016).
Wu, L., Waber, B. N., Aral, S., Brynjolfsson, E. & Pentland, A. Mining face-to-face interaction networks using sociometric badges: predicting productivity in an IT configuration task. Inf. Syst. Behav. Soc. Methods https://doi.org/10.2139/ssrn.1130251 (2008).
Paxton, A. & Dale, R. Argument disrupts interpersonal synchrony. Q. J. Exp. Psychol. 66, 2092–2102 (2013).
Alviar, C., Dale, R. & Galati, A. Complex communication dynamics: exploring the structure of an academic talk. Cogn. Sci. 43, e12718 (2019).
Joo, J., Bucy, E. P. & Seidel, C. Automated coding of televised leader displays: detecting nonverbal political behavior with computer vision and deep learning. Int. J. Commun. 13, 4044–4066 (2019).
Metallinou, A. et al. The USC CreativeIT database of multimodal dyadic interactions: from speech and full body motion capture to continuous emotional annotations. Lang. Res. Eval. 50, 497–521 (2016).
Pouw, W., Paxton, A., Harrison, S. J. & Dixon, J. A. Acoustic information about upper limb movement in voicing. Proc. Natl Acad. Sci. USA 117, 11364–11367 (2020).
Enfield, N., Levinson, S. C., De Ruiter, J. P. & Stivers, T. in Field Manual Vol. 10, 96–99 (ed. Majid, A.) (Max Planck Institute for Psycholinguistics, 2007).
Enfield, N. & Sidnell, J. On the concept of action in the study of interaction. Discourse Stud. 19, 515–535 (2017).
Duran, N. D., Paxton, A. & Fusaroli, R. ALIGN: analyzing linguistic interactions with generalizable techNiques — a Python library. Psychol. Methods 24, 419 (2019).
Brennan, S. E. & Clark, H. H. Conceptual pacts and lexical choice in conversation. J. Exp. Psychol. Learn. Mem. Cogn. 22, 1482–1493 (1996).
Hasson, U., Nir, Y., Levy, I., Fuhrmann, G. & Malach, R. Intersubject synchronization of cortical activity during natural vision. Science 303, 1634–1640 (2004).
Huth, A. G., De Heer, W. A., Griffiths, T. L., Theunissen, F. E. & Gallant, J. L. Natural speech reveals the semantic maps that tile human cerebral cortex. Nature 532, 453–458 (2016).
Shain, C. et al. Robust effects of working memory demand during naturalistic language comprehension in language-selective cortex. J. Neurosci. 42, 7412–7430 (2022).
Fedorenko, E., Blank, I. A., Siegelman, M. & Mineroff, Z. Lack of selectivity for syntax relative to word meanings throughout the language network. Cognition 203, 104348 (2020).
Stephens, G. J., Silbert, L. J. & Hasson, U. Speaker–listener neural coupling underlies successful communication. Proc. Natl Acad. Sci. USA 107, 14425–14430 (2010).
Schilbach, L. et al. Toward a second-person neuroscience. Behav. Brain Sci. 36, 393–414 (2013).
Redcay, E. & Schilbach, L. Using second-person neuroscience to elucidate the mechanisms of social interaction. Nat. Rev. Neurosci. 20, 495–505 (2019).
Riley, M. A., Richardson, M., Shockley, K. & Ramenzoni, V. C. Interpersonal synergies. Front. Psychol. 2, 38 (2011).
Dale, R., Fusaroli, R., Duran, N. D. & Richardson, D. C. in Psychology of Learning and Motivation (ed. Ross, B. H.) Vol. 59, 43–95 (Elsevier, 2013).
Fusaroli, R., Rączaszek-Leonardi, J. & Tylén, K. Dialog as interpersonal synergy. N. Ideas Psychol. 32, 147–157 (2014).
Hadley, L. V., Naylor, G. & Hamilton, A. F. D. C. A review of theories and methods in the science of face-to-face social interaction. Nat. Rev. Psychol. 1, 42–54 (2022).
Cornejo, C., Cuadros, Z., Morales, R. & Paredes, J. Interpersonal coordination: methods achievements and challenges. Front. Psychol. https://doi.org/10.3389/fpsyg.2017.01685 (2017).
Smaldino, P. E. in Computational Social Psychology 311–331 (Routledge, 2017).
Devezer, B., Nardin, L. G., Baumgaertner, B. & Buzbas, E. O. Scientific discovery in a model-centric framework: reproducibility, innovation, and epistemic diversity. PLoS One 14, e0216125 (2019).
Sulik, J., Bahrami, B. & Deroy, O. The diversity gap: when diversity matters for knowledge. Perspect. Psychol. Sci. 17, 752–767 (2022).
O’Connor, C. & Bruner, J. Dynamics and diversity in epistemic communities. Erkenntnis 84, 101–119 (2019).
Longino, H. in The Stanford Encyclopedia of Philosophy (ed. Zalta, E. N.) https://plato.stanford.edu/archives/sum2019/entries/scientific-knowledge-social/ (Stanford Univ., 2019).
Van Rooij, I. The tractable cognition thesis. Cogn. Sci. 32, 939–984 (2008).
Kwisthout, J., Wareham, T. & Van Rooij, I. Bayesian intractability is not an ailment that approximation can cure. Cogn. Sci. 35, 779–784 (2011).
Contreras Kallens, P. & Dale, R. Exploratory mapping of theoretical landscapes through word use in abstracts. Scientometrics 116, 1641–1674 (2018).
Methods for methods’ sake. Nat. Methods https://doi.org/10.1038/nmeth1004-1 (2004).
Oberauer, K. & Lewandowsky, S. Addressing the theory crisis in psychology. Psychon. Bull. Rev. 26, 1596–1618 (2019).
Meehl, P. E. Theory-testing in psychology and physics: a methodological paradox. Phil. Sci. 34, 103–115 (1967).
Klein, O. et al. A practical guide for transparency in psychological science. Collabra Psychol. 4, 20 (2018).
Muthukrishna, M. & Henrich, J. A problem in theory. Nat. Hum. Behav. 3, 221–229 (2019).
Eronen, M. I. & Bringmann, L. F. The theory crisis in psychology: how to move forward. Perspect. Psychol. Sci. https://doi.org/10.1177/1745691620970586 (2021).
Borsboom, D., van der Maas, H. L. J., Dalege, J., Kievit, R. A. & Haig, B. D. Theory construction methodology: a practical framework for building theories in psychology. Perspect. Psychol. Sci. https://doi.org/10.1177/1745691620969647 (2021).
Kyvik, S. & Reymert, I. Research collaboration in groups and networks: differences across academic fields. Scientometrics 113, 951–967 (2017).
Tebes, J. K. & Thai, N. D. Interdisciplinary team science and the public: steps toward a participatory team science. Am. Psychol. 73, 549 (2018).
Falk-Krzesinski, H. J. et al. Mapping a research agenda for the science of team science. Res. Eval. 20, 145–158 (2011).
da Silva, J. A. T. The Matthew effect impacts science and academic publishing by preferentially amplifying citations, metrics and status. Scientometrics 126, 5373–5377 (2021).
Scheel, A. M., Tiokhin, L., Isager, P. M. & Lakens, D. Why hypothesis testers should spend less time testing hypotheses. Perspect. Psychol. Sci. 16, 744–755 (2020).
Jones, M. N. Big Data in Cognitive Science (Psychology Press, 2016).
Paxton, A. & Griffiths, T. L. Finding the traces of behavioral and cognitive processes in big data and naturally occurring datasets. Behav. Res. Methods 49, 1630–1638 (2017).
Lupyan, G. & Goldstone, R. L. Beyond the lab: using big data to discover principles of cognition. Behav Res. Methods, 51, 1554–3528 (2019).
Haspelmath, M., Dryer, M. S., Gil, D. & Comrie, B. (eds) The World Atlas of Language Structures (Max Planck Digital Library, 2013).
Eberhard, D. M., Simons, G. F. & Fennig, C. D. Ethnologue: Languages of the World (SIL International, 2021).
MacCorquodale, K. & Meehl, P. E. On a distinction between hypothetical constructs and intervening variables. Psychol. Rev. 55, 95–107 (1948).
van Rooij, I. & Baggio, G. Theory before the test: how to build high-verisimilitude explanatory theories in psychological science. Perspect. Psychol. Sci. https://doi.org/10.1177/1745691620970604 (2021).
Christiansen, M. H. & Chater, N. Creating Language: Integrating Evolution, Acquisition, and Processing (MIT Press, 2016).
Berwick, R. C. & Chomsky, N. Why Only Us: Language and Evolution (MIT Press, 2016).
Gopnik, A. Scientific thinking in young children: theoretical advances, empirical research, and policy implications. Science 337, 1623–1627 (2012).
Pereira, A. F., James, K. H., Jones, S. S. & Smith, L. B. Early biases and developmental changes in self-generated object views. J. Vis. 10, 22–22 (2010).
Fagan, M. K. & Iverson, J. M. The influence of mouthing on infant vocalization. Infancy 11, 191–202 (2007).
Martin, J., Ruthven, M., Boubertakh, R. & Miquel, M. E. Realistic dynamic numerical phantom for MRI of the upper vocal tract. J. Imaging 6, 86 (2020).
Spivey, M. J. & Dale, R. Continuous dynamics in real-time cognition. Curr. Dir. Psychol. Sci. 15, 207–211 (2006).
Publication Manual of the American Psychological Association 3rd edn (American Psychological Association, 1983).
Publication Manual of the American Psychological Association 6th edn (American Psychological Association, 2010).
Ashby, W. R. An Introduction to Cybernetics (Martino, 1956).
de Raadt, J. D. R. Ashby’s law of requisite variety: an empirical study. Cybern. Syst. 18, 517–536 (1987).
Ward, L. M. Dynamical Cognitive Science (MIT Press, 2002).
Regier, T., Carstensen, A. & Kemp, C. Languages support efficient communication about the environment: words for snow revisited. PLoS One 11, e0151138 (2016).
Newell, A. Unified Theories of Cognition (Harvard Univ. Press, 1990).
Rich, P., de Haan, R., Wareham, T. & van Rooij, I. in Proc. Annual Meeting of the Cognitive Science Society Vol. 43, 3034–3040 (eds. Fitch, T., Lamm, C., Leder, H., and Teßmar-Raible, K.) (2021).
Potochnik, A. & Sanches de Oliveira, G. Patterns in cognitive phenomena and pluralism of explanatory styles. Top. Cogn. Sci. 12, 1306–1320 (2020).
Leydesdorff, L. & Schank, T. Dynamic animations of journal maps: indicators of structural changes and interdisciplinary developments. J. Am. Soc. Inf. Sci. Technol. 59, 1810–1818 (2008).
Leydesdorff, L. & Goldstone, R. L. Interdisciplinarity at the journal and specialty level: the changing knowledge bases of the journal Cognitive Science. J. Assoc. Inf. Sci. Technol. 65, 164–177 (2014).
DeStefano, I., Oey, L. A., Brockbank, E. & Vul, E. Integration by parts: collaboration and topic structure in the CogSci community. Top. Cogn. Sci. 13, 399–413 (2021).
Cummins, R. in Explanation And Cognition (eds Keil, F. C. & Wilson, R.) 117–144 (MIT Press, 2000).
Boyd, N. M. & Bogen, J. in Stanford Encyclopedia of Philosophy (ed. Zalta, E. N.) https://plato.stanford.edu/archives/win2021/entries/science-theory-observation/ (Stanford Univ., 2021).
Smaldino, P. E. How to build a strong theoretical foundation. Psychol. Inq. 31, 297–301 (2020).
Chang, H. Inventing Temperature: Measurement and Scientific Progress (Oxford Univ. Press, 2004).
A.S.W. was supported by the National Science Foundation (grants 1529127 and 1539129/1827744) and by the James S. McDonnell Foundation (https://doi.org/10.37717/220020507). K.L.J. was supported by the National Science Foundation (grant 2017245).
The authors declare no competing interests.
Peer review information
Nature Reviews Psychology thanks Berna Devezer; Michael Frank, who co-reviewed with Anjie Cao; and Justin Sulik for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Dale, R., Warlaumont, A.S. & Johnson, K.L. The fundamental importance of method to theory. Nat Rev Psychol 2, 55–66 (2023). https://doi.org/10.1038/s44159-022-00120-5