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Make ICC plots for your brms IRT models

solomonkurz.netlify.app · published 29 June 2021

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https://discourse.mc-stan.org/t/item-characteristic-curves-and-item-information-curves-from-item-response-models/22964
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https://r4ds.had.co.nz
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https://github.com/Lingtax/2018_measures_study
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https://osf.io/t9w2x/
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https://github.com/Lingtax/2018_measures_study/blob/master/Rcode/2018_Loram_CC_IRT.R
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https://bookdown.org/content/4857/monsters-and-mixtures.html
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https://bookdown.org/content/3686/ordinal-predicted-variable.html
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https://CRAN.R-project.org/package=tidybayes
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https://x.com/SolomonKurz/status/1409951540228628482?ref_src=twsrc%5Etfw
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https://solomonkurz.netlify.app/tags/bayesian
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https://solomonkurz.netlify.app/tags/brms
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https://solomonkurz.netlify.app/tags/plot
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https://solomonkurz.netlify.app/tags/tutorial
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Within-person factorial experiments, log(normal) reaction-time data Read at the source ↗
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Learn Stan with brms, Part III Read at the source ↗
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Learn Stan with brms, Part II Read at the source ↗
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https://github.com/paul-buerkner/brms
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https://solomonkurz.netlify.app/bookdown/
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https://www.thetaminusb.com/intro-measurement-r/
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http://arxiv.org/abs/1905.09501
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https://doi.org/10.18637/jss.v080.i01
doi.org
https://doi.org/10.32614/RJ-2018-017
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https://CRAN.R-project.org/package=brms
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https://sites.google.com/site/doingbayesiandataanalysis/
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https://doi.org/10.1016/j.jmva.2009.04.008
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https://doi.org/10.31234/osf.io/57nbk
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https://xcelab.net/rm/statistical-rethinking/
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https://www.R-project.org/
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https://www.springer.com/gp/book/9780387899756
springer.com
https://CRAN.R-project.org/package=tidyverse
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https://doi.org/10.21105/joss.01686
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