Dr Mircea Zloteanu 🌺🌞🍃

mzloteanu@mastodon.social

Posts

Post #4375963
📢 Excited about our (Louisa Kulke & Fatima Felisberti) new paper in Motivation & Emotion! It echoes a theme from my recent ISRE talk: rigorous methods, precise estimates, and theory-driven predictions are essential if we want cumulative emotion science. #emotion #bayesian #empathy #jasp #OpenScience #Preregistration #opendata #opencode https://link.springer.com/article/10.1007/s11031-026-10266-x
Post #2033916
#statstab #518 Before p &lt; 0.05 to Beyond p &lt; 0.05: Using History to Contextualize p-Values and Significance Testing Thoughts: An appropriate paper for today. #pvalues #teaching #history #pedagogy #nhst #fisher https://www.tandfonline.com/doi/pdf/10.1080/00031305.2018.1537891
Post #2033915
#statstab #519 Sensitivity Analysis and Robustness Checks Thoughts: Multiverse analysis allows you to capture decision uncertainty. #multiverse #jackknife #bias #robustness #sensitivity #r #outliers https://mike-data-analysis.share.connect.posit.cloud/sensitivity-analysis-and-robustness-checks.html
Post #2033914
#statstab #520 Reverse‐Bayes methods for evidence assessment and research synthesis Thoughts: I was reminded of this paper on assessing the evidentiary value of a finding. What do ppl think? #bayes #inference #evidence #probability #priors #sensitivity https://doi.org/10.1002/jrsm.1538
Post #2033913
#statstab #521 Non-adjustment for multiple testing in multi-arm trials of distinct treatments: Rationale and justification Thoughts: Most researchers struggle with multiplicity corrections. #error #bonferroni #FWER #FDR #falsepositive #nhst #alpha https://pmc.ncbi.nlm.nih.gov/articles/PMC7534018/
Post #2033912
#statstab #522 Bayes Rules! Different priors, different posteriors Thoughts: Nice illustration of how uninformative and informative priors change your posterior. #bayesian #dataviz #bayes #inference #sensitivity #priors https://www.bayesrulesbook.com/chapter-4#ch4-priors
Post #2033910
🚨 Come to iIIRG 2026 to hear our talk about better methods to analysing interview data! W/ Dr Cody Porter and @mattansb #belgium #conference #methods #investigativeinterview
Post #2033909
#statstab #523 Equal vs. Proportional Weighting in Least-Squares Means Thoughts: Interesting comparisons of bias for the two methods. Complex stuff. I wonder what people make of this. #weighting #error #bias #LSM #emmeans #covariates https://imazubi.github.io/stats/stats_equal_vs_proportional_lsm/index_equal_vs_proportional_lsm.html
Post #2033908
#524 Interactions in Logit Regressions: Why Positive May Mean Negative Thoughts: Nonlinear models require a bit more caution for new researchers when making inferences. #logit #inference #causalinference #interaction #datacolada https://datacolada.org/57
Post #2033907
#statstab #525 What Good Is a Regression? Inference to the Best Explanation and the Practice of Political Science Research Thoughts: It&#39;s interesting to see how other fields consider the problem of knowledge generation #polisci #epistemology #inference https://www.journals.uchicago.edu/doi/epdf/10.1086/734280
Post #2033906
#statstab #526 A Meta-Analysis of the Impact and Heterogeneity of Explicit Demand Characteristics Thoughts: The impact of the design on conclusions is under-appreciated #demandcharacteristics #design #methodology #error #bias #metascience #metaanalysis https://online.ucpress.edu/collabra/article/11/1/143005/212614/A-Meta-Analysis-of-the-Impact-and-Heterogeneity-of
Post #2033905
#statstab #527 t is for Trouble (and Textbooks): A Critique of Some Examples of the Paired-Samples t-test Thoughts: Some issues seem to reappear in the field. We need better training. #ttest #design #methods #error #analysis #repeatedmeasures #outliers https://www.jstor.org/stable/pdf/2987888.pdf?casa_token=cJM8NiLV_ygAAAAA:yWSbczJx4y1-PwhXptS3vh7mwzPzJ_VnUoF7w_v8yvKcY6kJku29daCauTL6V6tywgHdAPI8rAZqCLXgBsh873fRUXM8jjpbjRqN0AX-t8I3e-rXMQ
Post #2033904
#statstab #528 Survey Bot Detection Workshop Thoughts: &quot;Pick a cutoff value for detecting random responders&quot; can you spot the bots? #OpenScience #bots #detection #sample #human #participants #deception #shinyapp #education #tutorial https://falkcarl.shinyapps.io/BotApp1/
Post #2033903
#statstab #529 Understanding and misunderstanding randomized controlled trials Thoughts: Randomization is close to magic, but we still must be critical of our methods. #randomization #rct #design #critique #covariates #causalinference #ATE #confounder #bias https://doi.org/10.1016/j.socscimed.2017.12.005
Post #2033902
#statstab #530 Fisher vs Stouffer Thoughts: Combining p-values (say in a meta-analysis) is not a straightforward thing. Here are two methods. #fisher #stouffer #pvalues #metaanalysis #zscores #evidence #falsepositive #r #simulation https://timydaley.github.io/FisherVsStouffer.html
Post #2033901
#statstab #531 Using Extant Data to Improve Estimation of the Standardized Mean Difference Thoughts: I wonder if it&#39;s a good idea. Any edu/clinical people to chime in? Seems like using historic data. #smd #estimation #effectsize #variance #extantdata https://journals.sagepub.com/doi/10.3102/10769986241238478
Post #2033900
#statstab #523 Pre/Post design: the fallacy of comparing difference scores Thoughts: Another easy read on pre-post design and some concerns about change scores. #education #guide #prepost #ancova #change #ttest #design https://garstats.wordpress.com/2026/02/20/prepost/
Post #2033899
#statstab #524 {simglm}: Tidy simulation and power analyses Thoughts: As your design becomes more complex, simulation is the only way to go. #simulation #r #rstats #tidy #tidyverse #poweranalysis #design #tutorial https://simglm.brandonlebeau.org/