#statstab #424 Testing time: Carey-over effects and the (faulty) two-stage procedure Thoughts: An interesting post by Stephen Senn on how some "solutions" in testing make matters worse. #ttest #carryover #selection #history #design #methods errorstatistics.com/2020/10/28/s...

#statstab #422 Measuring Pickle Fanaticism: An Open Dataset for Teaching Instrument Development Thoughts: Teaching tool for learning about measurement validation and development. #mesurement #questionnaire #survey #psychometrics #efa #factoranalysis

#statstab #423 Second-generation p-values: Improved rigor, reproducibility, & transparency in statistical analyses Thoughts: I appreciated the thought behind sgpv but I've not seen them used anywhere. #sgpv #pvalue #error #bias #inference journals.plos.org/plosone/arti...

#statstab #421 Sample Size Planning for Statistical Power and Accuracy in Parameter Estimation Thoughts: AIPE is based on controlling the width of the CI. Sample size can be computed independent of effect size! #samplesize #confidenceintervals #AIPE #power www.annualreviews.org/content/jour...

#stats tip: Want to quickly approx the CIs for a reported effect? Goodman & Berlin ('94) to the rescue: - take the sample estimate and use the formulas for 80% and 90% power E.G. If authors anticipated a true δ=.50, obtained d=.40, then for 80%: 0.40 +- 0.7x0.5

#TodayinHistory #dataviz #OTD 📊 📅The First International Statistical Congress held on Sept 19, 1853 in Brussels, Belgium Organized mainly by Adolphe Quetelet; 26 countries sent representatives. Some main goals: standardization of measurements and tables; establish national statistical bureaus

#statstab #420 {misty} item.alpha: Coefficient Alpha, Hierarchical Alpha, and Ordinal Alpha Thoughts: If #419 and #418 made you consider reporting ordinal alpha, here is a package to do it #ordinal #likert #reliability #psychometrics #mesurement #rstats www.rdocumentation.org/packages/mis...

#statstab #419 A Measurement Is a Choice and Stevens’ Scales of Measurement Do Not Help Make It: A Response to Chalmers Thoughts: #418 convincing for not adopting ordinal α? This rebuttal may change your mind #ordinal #likert #mesurement #psychometrics doi.org/10.1177/0013...

#statstab #418 On Misconceptions and the Limited Usefulness of Ordinal Alpha Thoughts: Ordinal α seemed cool. Then I read this paper. Takeaway: methods need good peer review and debate. #ordinal #likert #cronbachalpha #reliability #methods doi.org/10.1177/0013...

#statstab #417 {pwrss} Practical Power Analysis in R Thoughts: Some useful vignettes for conducting power analyses for various designs, constraints, and data types. #poweranalysis #samplesize #r #power #guide #tutorial #sesoi #equivalence #tost #rstats cran.r-project.org/web/packages...

#stats Question: Does anyone have any good resources and insights for "multinomial processing tree" MPT models? Uses, limitations, theory, etc.

#statstab #416 Analysis of Means (ANOM) Concepts and Computations Thoughts: In-depth intro to ANOM from #415. Assumptions, designs, and extensions. Useful for ranking, error control, and answering "which group is not like the majority" #ANOM #tutorial digitalcommons.pvamu.edu/aam/vol16/is...

#statstab #415 Analysis of means: Examples using package ANOM Thoughts: Ever wonder why we run Analyses of Variance and not Means? Well, now you can do both! Using this #R package. #ANOM #ANOVA #lmer #means #ranking #design cran.r-project.org/web/packages...

Finished presenting at #eurocrim2025, with my partner in crime (research) Josh Bullock We expand our 2024 findings on the relationship bw #TrueCrime media, fear of victimhood, anxiety, and distrust in the Criminal Justice System using an experimental design. #greeece #athens

#statstab #414 The Bayes factor {shiny app} Thoughts: It's almost the start of term, so here is another teaching tool for learning about Bayes Factors. #nhbt #bayes #bayesfactor #learing #pedagogy #shiny #r statsedge.org/shiny/LearnBF/

Reviewer: “Have you considered…?” Me: Not only have I considered it, I cut 900 words on it last night.

#statstab #413 Counternull Sets in Randomized Experiments Thoughts: The counternull is a lost statistic, that is woefully underused when teaching stats. #counternull #nhst #pvalue #effectsize #teaching #randomization #rosenthal www.tandfonline.com/doi/pdf/10.1...

#statstab #412 Causal inference for N-of-1 trials Thoughts: Only skimmed this, curious what the #causalinference ppl think of this. #Nof1 #causalinference #ATE #effect #estimand #inference arxiv.org/abs/2406.103...

#statstab #411 Dynamic structural equation modeling [Hamaker et al] Thoughts: Has a great explanation for analysis N-of-1 studies. #Nof1 #bayesian #sem #modelling #tutorial #bookchapter www.statmodel.com/download/Ham...

Scott Aaronson's review of The Access Principle (www.scottaaronson.com/writings/jou...) hits hard: "what’s missing at this point is mostly anger--a justified response to being asked to donate our time, not to Amnesty International or the Sierra Club, but to the likes of Kluwer and Elsevier."

#statstab #410 Ordered Regression Models: a Tutorial Thoughts: A very comprehensive paper on analysing ordinal data. #orderedregression #regression #ordinal #tutorial #likert #probit #logit link.springer.com/article/10.1...

#statstab #409 Sensitivity Analyses for Unmeasured Confounders Thoughts: Some assumptions of obs. re. are untestable. One way around this is testing what could break your inference #causalinference #confounder #collider #bias #sensitivityanalysis #observational link.springer.com/article/10.1...

#statstab #408 Factor analysis: Overrated, Misused, But Still Useful Thoughts: Some scholars favour CFA over EFA, but this post reverses that perspective. Do you agree? #factoranalysis #cfa #efa #psychometrics #validity #mesurement esmitemrepositoryinfo.com/blog-posts#M...

#statstab #407 Choosing the Causal Estimand for Propensity Score Analysis of Observational Studies Thoughts: Doing obs. research? Do you know the difference b/w the ATE, ATT, ATU, and ATO? #observational #estimand #ATE #biomedical #clinical #effect arxiv.org/pdf/2106.105...

#statstab #406 The t-test tool Thoughts: "Stephen Senn describes the t-test, whose centenary he has celebrated in the previous article." @stephensenn.bsky.social #ttest #statistics #history #studentsttest #Gosset rss.onlinelibrary.wiley.com/doi/full/10....

#statstab #405 Best Practices for Estimating, Interpreting, and Presenting Nonlinear Interaction Effects Thoughts: Guidance on nonlinear interactions, reporting (probabilities) and visualisations. #probit #logit #logisticregression #nonlinear #guide sociologicalscience.com/download/vol...

#statstab #404 {latent2likert} simulate Likert response variables from hypothetical latent variables Thoughts: Most of psych is Likert type data. This R pkg can help simulate effects and check model fit. #likert #ordinal #r #latent #simulation #data latent2likert.lalovic.io/articles/usi...

#statstab #403 {CarefullyCausal} Provides estimates, assumptions and diagnostics for fixed-exposure causal analyses Thoughts: Really nice package for beginners in causal inference and observational studies. #causalinference #observational #r #teaching github.com/mauricekorf/...

#statstab #402 On Bayes factors for hypothesis tests {emBayes Factor} Thoughts: On bsky there were renewed debates about BFs. This paper provides "better" priors (mixture t centred on the ES). Also some p-value BFs #bayesian #bayesfactor #priors #cohend link.springer.com/article/10.3...

#statstab #401 Common issues, conundrums, and other things that might come up when implementing mixed models Thoughts: GLMMs are cool, but come with their own quirks. #glmm #lmer #brms #mixedeffects #hierarchicalmodels #r m-clark.github.io/mixed-models...

I love this. When people say you should think about your choice for CIs, this is what they mean.

Paper drop, for anyone interested in #metascience, #statistics, or #metaanalysis! @clintin.bsky.social and I show in a new paper in JASA that the P-curve, a popular forensic meta-analysis method, has deeply undesirable statistical properties. www.tandfonline.com/doi/full/10.... 1/?

It was a pleasure to discuss our latest employability research at the European Association of Psychology and Law conference. Paper is coming soon! #EAPL2025 #NotCurrentlySick

First day at #EAPL2025. Looking forward to some great talks, catching up with colleagues, and enjoying Vilnius! 🇱🇹

Hit 3k ♨️ Finally reaching my true potential: mid-tier Internet nuisance. Follow for more #stats and RM shenanigans!

1/ #APB Summer Showcase Day 12! Policing trauma isn’t just on the streets. Research by @drcodyporter.bsky.social & Paul Gavin shows how internal culture and management failures drive mental health issues, sometimes more than operational stress. 🧵👇

A short weekend post on a pet peeve of mine: likert questions substack.com/@mzloteanu/n... #substack #likert #design #science #research

📌 Research by: University of the West of England (Dr Cody Porter), King's College London (Dr Mircea Zloteanu) and Florida Institute of Technology (Dr Brandon May). Please feel free to share with relevant colleagues or networks! @mzloteanu.bsky.social

#statstab #400 (!) Precise Answers to Vague Questions: Issues With Interactions Thoughts: For the 400th post, I'll reshare an important article for the causal inference and interactions. #interactions #theory #methodology #psychology #researchmethods journals.sagepub.com/doi/10.1177/...

#statstab #399 An Illustrated Guide to TMLE, Part II: The Algorithm Thoughts: Targeted Maximum Likelihood Estimation. Not sure what this is or if I'll ever use it, but the tutorial seems straightforward. #guide #tutorial #TMLE #binary #ML www.khstats.com/blog/tmle/tu...

#statstab #398 Eta^2 for bayesian models {effectsize} Thoughts: Great resource, but scroll to "Eta Squared from Posterior Predictive Distribution" #effectsize #eta2 #bayesian #brms #r easystats.github.io/effectsize/r...

#statstab #397 How and Why I Switched from the ROC Curve to the Precision-Recall Curve to Analyze My Imbalanced Models Thoughts: Can the eyewitness peeps explain how they correct for stimuli imbalance? 🤔 #roc #roccurve #precisionaccuracy #auc juandelacalle.medium.com/how-and-why-...

#statstab #396 If researchers find Cohen’s d = 8, no they didn’t Thoughts: Sometimes an effect is so impressive that its unbelievable. #effectsize #cohend #QRPs #sesoi mmmdata.io/posts/2025/0...

#statstab #395 The n-of-1 randomized controlled trial: clinical usefulness Thoughts: Could RCTs comprised of 1 participant be useful? Maybe! And more so than large sample observational studies. #Nof1 #RCTs #causalinference #research #methods #clinical pubmed.ncbi.nlm.nih.gov/2297206/

#statstab #394 Difference-in-Differences Estimation Thoughts: A bit of love for the python coders. DiD with lots of examples and estimators. #did #python #guide #observational #TWFE #causalinference py-econometrics.github.io/pyfixest/dif...

#statstab #393 Statistically Efficient Ways to Quantify Added Predictive Value of New Measurements [actual post] Thoughts: #392 has the comments, but this is where the magic happens. #modelselection #modelcomparison #variance #effectsize #tutorial www.fharrell.com/post/addvalue/

#statstab #392 Statistically Efficient Ways to Quantify Added Predictive Value of New Measurements Thoughts: Forums can be great for asking the author for exact answers to complex questions #modelselection #causalinference #prediction #bias #information discourse.datamethods.org/t/statistica...

#statstab #391 {sensemakr} Sensitivity Analysis Tools for OLS Thoughts: No unobserved variables is an untestable assumption, but you can quantify the robustness of your ATE. #R #causalinference #observational #inference #confounding #bias #sensitivity carloscinelli.com/sensemakr/

Is a high VIF bad? Or is thinking about VIF bad? (spoiler: it's the latter)

Are you working on issues of replication and reproducibility of methodological research in psychology? Consider submitting a proposal to my call for papers, happy to chat about your ideas or answer any questions! www.psychologicalscience.org/publications...