Zobrazeno 1 - 10
of 622
pro vyhledávání: '"Shravan, Vasishth"'
Autor:
Audrey, Bürki, Shravan, Vasishth
With the pandemic, many experimental psychologists and linguists have started to collect data over the internet (hereafter on-line data). The feasibility of such experiments and the sample sizes required to achieve sufficient statistical power in fut
Externí odkaz:
http://arxiv.org/abs/2403.15459
Publikováno v:
Open Mind, Vol 6 (2024)
Externí odkaz:
https://doaj.org/article/0b7ff4add01c4441acadebc69b3dc581
Autor:
Robert, Christian P.
Publikováno v:
International Statistical Review / Revue Internationale de Statistique, 2011 Dec 01. 79(3), 486-487.
Externí odkaz:
http://dx.doi.org/10.1111/j.1751-5823.2011.00159_7.x
Publikováno v:
Neurobiology of Language, Vol 4, Iss 2, Pp 221-256 (2023)
AbstractIntuitively, strongly constraining contexts should lead to stronger probabilistic representations of sentences in memory. Encountering unexpected words could therefore be expected to trigger costlier shifts in these representations than expec
Externí odkaz:
https://doaj.org/article/a75e35dbb38a4704af321e42cf46f844
Autor:
Christian P. Robert
Publikováno v:
International Statistical Review. 79:486-487
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c2060a66c02b5b284e27408a552b25f
https://doi.org/10.1111/j.1751-5823.2011.00159_7.x
https://doi.org/10.1111/j.1751-5823.2011.00159_7.x
Publikováno v:
PLoS ONE, Vol 17, Iss 8 (2022)
In this paper we examine the effect of uncertainty on readers’ predictions about meaning. In particular, we were interested in how uncertainty might influence the likelihood of committing to a specific sentence meaning. We conducted two event-relat
Externí odkaz:
https://doaj.org/article/df4bc6350826438aab38e8ed8eb401c8
Publikováno v:
Open Mind (2021)
Externí odkaz:
https://doaj.org/article/17fad58140a24527bc10b31b68cdd027
Autor:
Johnny van Doorn, Julia M. Haaf, Angelika Marlene Stefan, Eric-Jan Wagenmakers, Gregory Edward Cox, Clintin P. Davis-Stober, Andrew Heathcote, Daniel W. Heck, Michael Kalish, David Kellen, Dora Matzke, Richard Donald Morey, Bruno Nicenboim, Don van Ravenzwaaij, Jeffrey N. Rouder, Daniel Schad, Rich Shiffrin, Henrik Singmann, Shravan Vasishth, João Veríssimo, Florence Bockting, Suyog Chandramouli, John C Dunn, Quentin Frederik Gronau, Maximilian Linde, Sara D McMullin, Danielle Navarro, Martin Schnuerch, Himanshu Yadav, Frederik Aust
Publikováno v:
Computational Brain and Behavior, 6(1). Springer
van Doorn et al. (2021) outlined various questions that arise when conducting Bayesian model comparison for mixed effects models. Seven response articles offered their own perspective on the preferred setup for mixed model comparison, on the most app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::913478eb8d898d23dae77ff0f528e81d
https://doi.org/10.1007/s42113-022-00160-3
https://doi.org/10.1007/s42113-022-00160-3
Autor:
Shravan Vasishth
Publikováno v:
MethodsX, Vol 7, Iss , Pp 100850- (2020)
A commonly used approach to parameter estimation in computational models is the so-called grid search procedure: the entire parameter space is searched in small steps to determine the parameter value that provides the best fit to the observed data. T
Externí odkaz:
https://doaj.org/article/10b41b74715f4237acccbb2ee3c6da59
Publikováno v:
Psychological Methods, 1-24. AMER PSYCHOLOGICAL ASSOC
STARTPAGE=1;ENDPAGE=24;ISSN=1082-989X;TITLE=Psychological Methods
STARTPAGE=1;ENDPAGE=24;ISSN=1082-989X;TITLE=Psychological Methods
Inferences about hypotheses are ubiquitous in the cognitive sciences. Bayes factors provide one general way to compare different hypotheses by their compatibility with the observed data. Those quantifications can then also be used to choose between h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9f0705fb6092df63195d3a70f4f497c
https://doi.org/10.1037/met0000472
https://doi.org/10.1037/met0000472