#stats Q: for a bayesian negative binomial (in #brms), who should I think about the prior on phi (shape)? How can I connect it to either theory or stat desiderada? Examples, tutorials, resources appreciated (it all seems a bit abstract to me)

#statstab #460 {permuco} permutation tests in linear models with nuisances variables Thoughts: Supports ANOVA, ANCOVA, t-tests and more. #permutation #randomization #ANOVA #rstats #r #pvalues #ancova #ttest jaromilfrossard.github.io/permuco/inde...

#statstab #459 Getting Comfortable with Expressing Beliefs as Distributions Thoughts: Bayesian stats requires a good understanding of priors, but these are often unintuitive. Plots help. #bayesian #priors #ggplot #r #dataviz #learing #education brian-lookabaugh.github.io/website-bria...

This year I'm teaching an advanced stats course for our psych grad students, and I want to squeeze as much causal stuff as I can - but there's just too much! ATE, DAGs, confounder selection, table 1 & 2 fallacies, collider bias, ... What else should I squeeze in there?

#statstab #458 Causal inference for observational data using {modelbased} Thoughts: IPW, g-computation, and more. Learning OS and ways to compute ATE for (more accurate, but still not great) inference. #gcomputation #ipw #iptw #observational #inference easystats.github.io/modelbased/a...

#statstab #457 Using color packages Thoughts: Some package ideas to make your {ggplot2} figures more interesting. #dataviz #ggplot #r #figures #plots bookdown.org/hneth/ds4psy...

#statstab #456 Shall we count the living or the dead? Thoughts: survival ratio -> if the intervention increases risk of the outcome risk ratio -> if the intervention reduces risk of the outcome #causalinference #riskratios #survivalanalysis #estimand arxiv.org/abs/2106.063...

#statstab #455 {plotROC} Generate ROC Curve Charts for Print and Interactive Use Thoughts: I dislike ROC curves, just check out the way you show uncertainty on them. #roc #auc #roccurve #specificity #sensitivity #signaldetection #sdt #ggplot #r sachsmc.github.io/plotROC/arti...

Maybe if statisticians started every sentence with "Yes, you are right. Let me do that for you"

#statstab #454 {Projoint} The One-Stop Conjoint Shop Thoughts: Conjoint analyses will be the future for many (once they figure out what they are) #conjointanalysis #rstats #r #groupanalysis yhoriuchi.github.io/projoint/ind...

Can you spot a traitor? Unlikely. But can someone's demeanour affect our perception of them? I contributed to this @BBC piece relating to the finally of #CelebrityTraitors #TheTraitors #bbc #liedetection www.bbc.co.uk/news/resourc...

#statstab #453 {Bayes Power} A General Application of Power and Sample Size Calculation for the Bayes Factors Thoughts: Blending frequentist notions of power with bayes hypothesis testing. #poweranalysis #bayesian #bayesfactor #errorrate #rstats #nhbt doi.org/10.31234/osf...

#statstab #452 Assumption Checking Prevents Assumption Hacking in Multiverse Meta-Analyses Thoughts: Heterogeneity, publication bias, multiverse analysis, z-curve and more. #zcurve #multiverse #heterogeneity #metaanalysis #bias #publicationbias replicationindex.com/2025/06/13/a...

📄 New paper out: Behind Bars and Lies Are good liars also good lie detectors? Not really, but it depends; for prisoners there was little evidence for a “deception-general” ability. For the public, we find moderate evidence for one. See full paper: onlinelibrary.wiley.com/doi/10.1002/...

#statstab #451 Weighted Brier Score Thoughts: Prediction is important for some research questions (e.g. clinical). But the standard one has some limitations. #prediction #brierscore #auc #clinical #risk arxiv.org/html/2408.01...

#statstab #450 Fitting GAMs with brms Thoughts: Assuming linearity of your continuous predictors is not needed when you can add wiggles! #gam #glmm #linearmodel #modelling #brms #rstats #bayes #tutorial #splines #r fromthebottomoftheheap.net/2018/04/21/f...

#statstab #449 Significance tests, p-values, and falsificationism Thoughts: A statistician and a philosopher debate p-values (not the setup to a joke). Good thread. #pvalues #significance #nhst #fisher #greenland #epistemology #statistics discourse.datamethods.org/t/significan...

#statstab #448 {metaforest} Small sample meta-analysis Thoughts: "a machine-learning based, exploratory approach to identify relevant moderators in meta-analysis" #ML #MachineLearning #metaanalysis #smallsample #samplesize #heterogeneity #moderator cjvanlissa.github.io/metaforest/a...

I am hiring PhD candidates to study the psychology of attention & technology use at @tilburg-university.bsky.social. We're looking for motivated & curious scholars with expertise in cognitive psychology and statistics, and offer a friendly work environment with great terms & benefits. tiu.nu/22989

New release of PowerLMM.js! Browser-based power analysis for longitudinal models with dropout. Now includes: - Power analysis summary report - Reproducible & shareable configs (URL/JSON) - Calculations validated against R - Hypothesis region visualization powerlmmjs.rpsychologist.com

#statstab #447 Why do we use a one-tailed test F-test in analysis of variance (ANOVA)? Thoughts: Directional tests are not the same things as one-tailed tests! Confusing at first. #onetailed #directional #Ftest #ANOVA #chisquared stats.stackexchange.com/questions/67...

#statstab #446 {causaldata} Packages of Example Data for The Effect Thoughts: On your journey to learning Causal Inference you can use some nice datasets to figure out how horrible it can all go. #causalinference #observational #python #r #DAG #OS github.com/NickCH-K/cau...

After years of seeing people apply t-test to every data type, design, and question under the sun in psychology, yeah I do have a visceral reaction to it!

#statstab #445 What are credible priors and what are skeptical priors? Thoughts: An excellent thread on prior elicitation by some of the big names in the field (frequentist and bayesian). #priors #bayesian #bayes #likelihood #medicine #clinical #debate discourse.datamethods.org/t/what-are-c...

It also reminded me of the “stats maven” concept coined by @sanjaysrivastava.com some very long time ago, I believe here? thehardestscience.com/2014/12/04/s...

#samplesize and #ethics question: You plan for a study needing n=100 (50 per cell). Power analysis is all set up and pre-reg. But, because you do research in a uni, you are told you need to allow for more participants (students) as there is a set number of credits all need to reach. What do you do?

A: The study is OBS, so we must be cautious in our inference B: But wait, we have thousands of data points! A: Why didn't you say that from the start!? Then it's all good! We can conclude whatever! B: INDEED, everyone knows when N is big randomization isn't needed! * everyone cheers *

#statstab #444 {popower}: Power and Sample Size for Ordinal Response Thoughts: Not the most intuitive but useful if you know the DGP will use ordinal data. #ordinal #poweranalysis #power #effectsize #rstats #stats rdrr.io/cran/Hmisc/m...

🎉🍻🥳 Thank you all for subscribing. More posts to come this year. Subscribe now: mzloteanu.substack.com #substack #statstab #statistics #FiguringStuffOut

#statstab #443 Dienes Bayes factor calculator Thoughts: Dienes presents a different way to compute BFs using the sample data. But, this can be seen as an acceptable double-dipping. #bayesian #bayesfactor #evidence #likelihood #guide bencepalfi.shinyapps.io/Dienes_BF_ca...

Can you predict when Lou Bega's greatest hit, Mambo No. 5, was released based on the names of all the women mentioned in the song? Weirdly yes. yawpr.substack.com/p/project-a-... #databs #rstats

“Correlation is causation” 😈 New #substack going over the maths of correlation, t-test, and linear models. open.substack.com/pub/mzlotean... #correlation #causalinference #effects #pearson #ttest

#statstab #442 Understanding uncertainty in school league tables Thoughts: Rankings are virtually meaningless, especially neighbour values. #ranking #comparison #uncertainty #QRPs #education #academia research-information.bris.ac.uk/ws/portalfil...

#statstab #441 Bayes-by Shower Thoughts: Comprehensive (read: long) tutorial on bayesian analysis and how to think about research. #bayes #rstats #bayesian #tutorial #DAGs #estimand #observational #design betanalpha.github.io/assets/chapt...

#statstab #440 Computing Statistical Power for the Difference in Differences Design Thoughts: DiD studies are all the rage in Obs research. But how does the concept of power apply to them? #poweranalysis #DiD #causalinference #samplesize #observational journals.sagepub.com/doi/10.1177/...

#stats A less discussed issue of a focus on p<.05: a Research is likely to recheck their analysis/data for "errors" if they find p=.06, but would not think to do so if p=.01. You could have *real* errors in both scenarios, but one aligns more with your goals.

#statstab #439 {ZOID} Thoughts: "zero-and-one inflated Dirichlet regression (also known as trinomial mixture models) in a Bayesian framework (Stan)" Useful for composite proportions. #Dirichlet #bayesian #stan #r #rstats #proportions noaa-nwfsc.github.io/zoid/index.h...

#statstab #438 Introduction to {DataSetsVerse} Thoughts: It's full teaching season, so here is a package with datasets to use. Covers Crim, Econ, Med and more. #r #rstats #education #pedagogy #teaching #opendata #OpenScience #data #datasets lightbluetitan.github.io/datasetsverse/

Results of the replication are in! Chocolate is more desirable than poop: Cohen's d_rm = 6.20, 95%CI [5.63, 6.78] N = 486, two single item 1-7 Likert scales of desirability. w/ @jamiecummins.bsky.social

Footnote 4 is an important point to keep in mind when reading this.

#statstab #437 Speeding up categorical models in {brms} Thoughts: As I'm currently annoyed with how long some models take, I'm sharing resources to help others. By @matti.vuorre.com #brms #categorical #efficiency #rstats #modelling #r #stan rpubs.com/mvuorre/fast...

#statstab #436 {chkptstanr} Checkpoint MCMC Sampling with Stan Thoughts: This! Allows you to stop and start the sampling in {brms}. Can be a lifesaver. #rstats #stan #brms #mcmc #efficiency #stanr #hmc #bayesian donaldrwilliams.github.io/chkptstanr/

This is what I find awesome (in the truest sense) about scientific development in the modern age. One group posts a new technique and within a few days it is implemented by others. #rstats is magic (and efficient)

#statstab #435 Guide to understanding the intuition behind the Dirichlet distribution Thoughts: Useful for composite proportions, but take ages in brms. #brms #Dirichlet #proportions #modelling #rstats #r #betareg www.andrewheiss.com/blog/2023/09...

R: How many cores do you want to use? Me: Yes. #R #brms #bayesian #rstats

#statstab #434 Exposing omitted moderators: Explaining why effect sizes differ in the social sciences Thoughts: Maybe our models are too simple to makdle the generalisable claims we want. #bias #moderator #causalinference #heterogeneity #effect doi.org/10.1073/pnas...

#statstab #433 The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients Thoughts: Adding predictors to your model results in marked changes in inference. Be mindful! #table2 #fallacy #covariates #bias #inference #regression doi.org/10.1093/aje/...

#statstab #432 PsychOpen Gold Thoughts: instead of submitting to greedy and unhelpful publishers, try this list of fully open and free journals in psychology. #OpenScience #openaccess #apcs #goldaccess #pedagogy psychopen.eu

100% this, especially with Wiley given their anti-preprint stance.

We're looking for an experimental psychologist in Witten. Contact me if you have questions about the job (I'm not on the commission, so can talk freely :-) uni-wh.softgarden.io/job/59638545...