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Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #328 How to Assess Task Reliability using Bayesian Mixed Models by @Dom_MakowskiThoughts: Nice walkthrough using {brms}, with code, data gen, and plots.<a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#r</a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayesian</a> <a href="https://mastodon.social/tags/mixedeffects" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#mixedeffects</a> <a href="https://mastodon.social/tags/reliability" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#reliability</a> <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a><a href="https://realitybending.github.io/post/2024-03-18-signaltonoisemixed/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://realitybending.github.io/post/2024-03-18-signaltonoisemixed/</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #299 The role of "max_treedepth" in No-U-Turn?Thoughts: Once you start using more complex models you will run into issues at some point; this is one; good solution guide.<a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayesian</a> <a href="https://mastodon.social/tags/modeling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#modeling</a> <a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stats</a> <a href="https://mastodon.social/tags/issues" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#issues</a> <a href="https://mastodon.social/tags/solutions" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#solutions</a> <a href="https://mastodon.social/tags/stan" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stan</a> <a href="https://mastodon.social/tags/forum" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#forum</a><a href="https://discourse.mc-stan.org/t/the-role-of-max-treedepth-in-no-u-turn/24155" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://discourse.mc-stan.org/t/the-role-of-max-treedepth-in-no-u-turn/24155</a>

Pierre de VillemereuilIncidentally, our companion <a href="https://ecoevo.social/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#rstats</a> Reacnorm package is now live in CRAN, so it's as easy as `install.packages("Reacnorm")` and `vignette("TutoReacnorm")` to access our nice tutorial on analyse reaction norms using the <a href="https://ecoevo.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> and Reacnorm package.<a href="https://cran.r-project.org/package=Reacnorm" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://cran.r-project.org/package=Reacnorm</a>

Christian RöverA very interesting workshop on "Hierarchical models in preclinical research" finished today in Göttingen. This was a joint undertaking of the IBS-DR working groups "Non-clinical statistics" and "Bayes Methods", and included an extensive Tutorial on <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> by Sebastian Weber and Lukas Widmer. Some of the material is available on the meeting website:<a href="https://www.biometrische-gesellschaft.de/arbeitsgruppen/bayes-methodik/workshops/2024-goettingen.html" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://www.biometrische-gesellschaft.de/arbeitsgruppen/bayes-methodik/workshops/2024-goettingen.html</a><a href="https://mastodon.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Bayesian</a> <a href="https://mastodon.social/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#rstats</a> <a href="https://mastodon.social/tags/MedStatGoe" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MedStatGoe</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #228 Applied Modelling in Drug Development - Setting priors in {brms}Thoughts: Part of a larger book, useful bit for understanding how to set priors & check them for bayesian models & meta-analyses<a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stats</a> <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/priors" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#priors</a> <a href="https://mastodon.social/tags/metaanalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#metaanalysis</a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayesian</a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#r</a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayes</a> <a href="https://mastodon.social/tags/drugs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#drugs</a> <a href="https://mastodon.social/tags/clinicaltrials" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#clinicaltrials</a> <a href="https://opensource.nibr.com/bamdd/src/01c_priors.html" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://opensource.nibr.com/bamdd/src/01c_priors.html</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #227 Parameterization of Response Distributions in {brms}Thoughts: If you use <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> and can read mathematical notation (who can't, right?), this page will be useful.<a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#r</a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayes</a> <a href="https://mastodon.social/tags/models" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#models</a> <a href="https://mastodon.social/tags/distributions" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#distributions</a> <a href="https://mastodon.social/tags/likelihood" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#likelihood</a> <a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stats</a><a href="https://cran.r-project.org/web/packages/brms/vignettes/brms_families.html" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://cran.r-project.org/web/packages/brms/vignettes/brms_families.html</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #221 <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> posterior_epred() vs posterior_predict()Thoughts: When starting off with bayesian mixed models you'll run across this issue. Here's one of the best forum posts on it.<a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayesian</a> <a href="https://mastodon.social/tags/mixedeffects" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#mixedeffects</a> <a href="https://mastodon.social/tags/models" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#models</a> <a href="https://mastodon.social/tags/posterior" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#posterior</a> <a href="https://mastodon.social/tags/effects" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#effects</a> <a href="https://mastodon.social/tags/prediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#prediction</a><a href="https://discourse.mc-stan.org/t/confusion-on-difference-between-posterior-epred-and-posterior-predict-in-a-mixed-effects-modelling-context/28813" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://discourse.mc-stan.org/t/confusion-on-difference-between-posterior-epred-and-posterior-predict-in-a-mixed-effects-modelling-context/28813</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stats</a> Q about sum scores: Is it better to analyse sum scores (4 items, range 4-20) using a cumulative model or a ordered beta? And how can i compare fit bw the two? just loo? <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/orderedbetareg" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#orderedbetareg</a> <a href="https://mastodon.social/tags/sumscores" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#sumscores</a>

Ross GaylerOnline free book: Introduction to Bayesian Data Analysis for Cognitive Science<a href="https://bayes.club/@ShravanVasishth/113330289055047281" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://bayes.club/@ShravanVasishth/113330289055047281</a><a href="https://aus.social/tags/bayes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayes</a> <a href="https://aus.social/tags/Rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Rstats</a> <a href="https://aus.social/tags/STAN" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#STAN</a> <a href="https://aus.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://aus.social/tags/OpenAccess" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#OpenAccess</a> <a href="https://aus.social/tags/OA" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#OA</a> <a href="https://aus.social/tags/CognitiveScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#CognitiveScience</a> <a href="https://aus.social/tags/CogSci" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#CogSci</a> <a href="https://a.gup.pe/u/cogsci" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@cogsci</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #201 Missing Data and DAGs and other stuffThoughts: <a href="https://mastodon.social/tags/missingdata" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#missingdata</a> is difficult to handle, but maybe if we build theoretical models using <a href="https://mastodon.social/tags/DAGs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DAGs</a> will help. Also measurement error. <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/rethinking" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#rethinking</a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#r</a> <a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stats</a> <a href="https://mastodon.social/tags/mice" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#mice</a> <a href="https://mastodon.social/tags/measurement" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#measurement</a> <a href="https://mastodon.social/tags/error" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#error</a><a href="https://bookdown.org/content/4857/missing-data-and-other-opportunities.html#measurement-error" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://bookdown.org/content/4857/missing-data-and-other-opportunities.html#measurement-error</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #198 Bayesian mixed effects (aka multi-level) ordinal regression models with {brms}Thoughts: Useful tutorial also for frequentists, as it covers checking multiple links at once in {ordinal}.<a href="https://mastodon.social/tags/ordinal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ordinal</a> <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/clmm" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#clmm</a> <a href="https://mastodon.social/tags/probit" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#probit</a> <a href="https://mastodon.social/tags/cloglog" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#cloglog</a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#r</a> <a href="https://mastodon.social/tags/cauchit" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#cauchit</a><a href="https://kevinstadler.github.io/notes/bayesian-ordinal-regression-with-random-effects-using-brms/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://kevinstadler.github.io/notes/bayesian-ordinal-regression-with-random-effects-using-brms/</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #181 Comparing Bayesian Approaches by @jebyrnesThoughts: Compares running models in <a href="https://mastodon.social/tags/rethinking" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#rethinking</a>, <a href="https://mastodon.social/tags/stan" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stan</a>, <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a>, <a href="https://mastodon.social/tags/inla" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#inla</a>, and <a href="https://mastodon.social/tags/glmmTMB" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#glmmTMB</a> via <a href="https://mastodon.social/tags/TMBstan" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#TMBstan</a>. It's nice to have options.<a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayes</a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayesian</a> <a href="https://mastodon.social/tags/rstan" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#rstan</a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#r</a> <a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stats</a> <a href="https://mastodon.social/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#rstats</a><a href="https://biol609.github.io/lab/alt_to_rethinking.html" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://biol609.github.io/lab/alt_to_rethinking.html</a>

Dr Mircea Zloteanu 🌼🐝oh, low E-BFMI warning ⚠, why do you persist? just let me sleep...<a href="https://mastodon.social/tags/stan" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#stan</a> <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/modelwoes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#modelwoes</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #169 {priorsense} prior diagnostics and sensitivity analysisThoughts: Bayesian modelling requires more scrutiny of how one's choices impact outcomes. This packages has handy functions + plots.<a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayesian</a> <a href="https://mastodon.social/tags/rstan" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#rstan</a> <a href="https://mastodon.social/tags/priors" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#priors</a> <a href="https://mastodon.social/tags/mcmc" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#mcmc</a> <a href="https://mastodon.social/tags/diagnostics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#diagnostics</a><a href="https://n-kall.github.io/priorsense/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://n-kall.github.io/priorsense/</a>

Mario Angst<a href="https://rstats.me/@danwwilson" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@danwwilson</a> <a href="https://genomic.social/@lwpembleton" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@lwpembleton</a> <a href="https://fediscience.org/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> by <a href="https://fosstodon.org/@paul_buerkner" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@paul_buerkner</a> has made Bayesian models incredibly fun and intuitive for me. I love the combination of well thought out defaults and API with a lot of depth and power, should you need it. Other than that, I think <a href="https://fediscience.org/tags/lubridate" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#lubridate</a> needs some love! Oh and <a href="https://fediscience.org/tags/igraph" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#igraph</a>, which just works ™️ plus it's lovely descendant <a href="https://fediscience.org/tags/tidygraph" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#tidygraph</a> 🕸️ <a href="https://fediscience.org/tags/packagelove" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#packagelove</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #164 Ordinal regression models to analyze Likert scale dataThoughts: One of the clearest tutorial for ordinal, cumulative (probit), models I've seen. Reports probabilities and expected mean ratinga, w/ plots!<a href="https://mastodon.social/tags/ordinal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ordinal</a> <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/likert" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#likert</a> <a href="https://mastodon.social/tags/probit" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#probit</a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#r</a><a href="https://dibsmethodsmeetings.github.io/ordinal-regression/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://dibsmethodsmeetings.github.io/ordinal-regression/</a>

Gabe WinterFirst version of my first <a href="https://ecoevo.social/tags/R" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#R</a> package is out and working! 🥳 <a href="https://gabewinter.github.io/VarDecomp/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://gabewinter.github.io/VarDecomp/</a>It has functions to: - produce and evaluate <a href="https://ecoevo.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> models - do variance decomposition - summarize and plot results Let me know if you have some data to test it out and help improve it!

Francisco Rodriguez-SanchezJust added support for multivariate (multiresponse) models to {DHARMa.helpers}, the <a href="https://ecoevo.social/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#rstats</a> package that facilitates checking <a href="https://ecoevo.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Bayesian</a> <a href="https://ecoevo.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> models with {DHARMa}<a href="https://pakillo.github.io/DHARMa.helpers/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://pakillo.github.io/DHARMa.helpers/</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #119 A hands-on example of Bayesian mixed models with {brms}Thoughts: Initially, I found this guide to be difficult, but as my knowledge grew I realised the usefulness of wrangling the posterior directly to answer specific questions.<a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#r</a><a href="https://bayesat.github.io/lund2018/slides/andrey_anikin_slides.pdf" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://bayesat.github.io/lund2018/slides/andrey_anikin_slides.pdf</a>

Dr Mircea Zloteanu 🌼🐝<a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#statstab</a> #111 Bayesian statistics resources [quick guide] <a href="https://rogue-scholar.social/@andrewheiss" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@andrewheiss</a> Thoughts: An excellent short guide to conducting/reporting bayesian analyses. Inc. theoretical diff. you need to be aware of, PD, ROPE, CrI, etc. <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#brms</a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#bayesian</a> <a href="https://mastodon.social/tags/tutorial" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#tutorial</a> <a href="https://mastodon.social/tags/guide" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#guide</a><a href="https://evalf21.classes.andrewheiss.com/resource/bayes/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://evalf21.classes.andrewheiss.com/resource/bayes/</a>

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