#statstab #635 Standardization and other approaches to meta-analyze differences in means

Thoughts: A good resource for selecting the standardiser in your SMD & comments for the {metafor} pkg.

#metaanalysis #smd #effectsize #cohend #bias #heterogeneity

onlinelibrary.wiley.com/doi/10.1002/...

#statstab #634 Standardized Regression Coefficients: A Further Critique and Review of Some Alternatives

Thoughts: Devastating critique of SMDs (e.g. Cohen's d or Pearson's r).

#smd #cohend #effectsize #estimand #standardization #covariates #ancova #SD

www.ovid.com/jnls/epidem/...

#statstab #633 The Well-Adjusted Statistician: Analysis of Covariance Explained

Thoughts: Randomization +ANCOVA. Inc prognostic covariates improves precision
#ancova #randomization #confidenceintervals #experiment #inference #precision #covariates
www.appliedclinicaltrialsonline.com/view/well-ad...

#statstab #632 Decline effects, statistical artifacts, and a meta-analytic paradox

Thoughts: Plz don't flip/reverse your effects without thinking about the scale!

#metaanalysis #bias #error #effectsize #effects #critique #artifact

raw.githubusercontent.com/richarddmore...

#statstab #631 Prior Information in Frequentist Research Designs: The Case of Neyman’s Sampling Theory

Thoughts: Model-based v design-based problem. This should be discussed more.

#modelbased #designbased #sampling #priors #neyman #frequentist #bayesian

link.springer.com/article/10.1...

#statstab #630 A Tutorial on Distribution-Free Uncertainty Quantification Using Conformal Prediction

Thoughts: Conformal predictions are getting more popular.

#conformalprediction #frequentist #uncertainty #assumptions #distributions #tutorial

doi.org/10.1177/2515...

#statstab #629 Extreme-Value Signal Detection Theory For Recognition Memory: The Parametric Road Not Taken

Thoughts: Let's get ready to Gumbel!

#sdt #theory #modelling #gumbel #methods #statistics #tutorial #memory #discrimination

osf.io/preprints/ps...

#statstab #628 Meta-analysis models relaxing the random-effects normality assumption: methodological systematic review and simulation study

Thoughts: Looks interesting, the little I get.

#metaanalysis #methods #statistics #assumptions
#randomeffects

link.springer.com/article/10.1...

#statstab #627 Elegant theories and the problems of social psychology

Thoughts: Why do we expect theories in psych to be "elegant"?

#theory #research #debate #perspective #psychology #socialpsychology #metapsychology #parsimony #evidence #critique

www.tandfonline.com/doi/full/10....

#statstab #626 Goal-Driven Flexible Bayesian Design

Thoughts: Bayes allows you to design informative studies and anticipate issues.

#bayesian #bayes #design #simulation #rct #tutorial #inference #mcid #equivalence #efficacy #estimation #noninferiority

hbiostat.org/bayes/design

#statstab #625 {lavinteract}: Post-Estimation Utilities for 'lavaan' Fitted Models

Thoughts: "Companion toolbox for structural equation models fitted with 'lavaan'"

#lavaan #sem #modelselection #modelfit #r2 #FDR #VIF #latent #rstats #r

cran.r-project.org/web/packages...

#statstab #624 Severe Testing:
Error Statistics versus Bayes Factor Tests

Thoughts: This seems to be the framework most NHST researchers are adopting.

#nhst #hypothesis #hypothesistesting #severetestting #equivalence #sesoi #methods #frequentist

doi.org/10.1086/736950

#statstab #623 Six Lemmas Concerning Heterogeneity and Nonlinearity in Causal Inference

Thoughts: A very clear treaty of Causal inference problems.

#causalinference #ATE #MachineLearning #inference #bias #heterogeneity #lemma #nonlinear #observational

math.la.asu.edu/~prhahn/six-...

#statstab #622 Some notes on probability judgement

Thoughts: The position of an answer can be more informative than it's correctness.

#probability #psychology #bias #surveys #calibration #error

blog.djnavarro.net/posts/2025-0...

#statstab #621 A General Method For Estimating Reliability Using Bayesian Measurement Uncertainty

Thoughts: "estimating reliability [...] for complex cognitive and behavioural assessments without test-retest data" wow!

#reliability #bayesian #testretest

doi.org/10.31234/osf...

#statstab #620 Why is the Tukey's IQR not used in the R program?

Thoughts: R has many ways to compute IQR and the default isn't what you'd probably get by hand.

#iqr #rstats #forum #discussion #crossvalidated #tukey #robust #quantile #descriptives

stats.stackexchange.com/questions/60...

#statstab #619 Generalized Linear Models: Linear regression with counts, ratios, binary outcomes and more

Thoughts: Good teaching/learning resource
#glm #education #guide #resources #rstats #r #linearmodel #regression #nonlinear #poisson #count #binomial

fransrodenburg.github.io/Applied-Stat...

#statstab #618 True and false interindividual differences in the physiological response to an intervention

Thoughts: Not all individual participant/data plots show what you think.

#dataviz #plots #variance #variability #randomization #heterogeneity

physoc.onlinelibrary.wiley.com/doi/ftr/10.1...

#statstab #617 Why Adjusted Regression Coefficients Are Less Descriptive Than They Look

Thoughts: Great overview of the "controlling for" issue in multiple regression

#regression #inference #covariates #multivariable #guide #adjustment #causalinference

rpsychologist.com/descriptive-...

#statstab #616 The brms Book: Applied Bayesian Regression
Modelling Using R and Stan (Early Draft)

Thoughts: {brms} is a main package fir bayesian stats. A must to know.

#brms #bayes #bayesian #modelling #book #tutorial #regression #stan #rstats #r

paulbuerkner.com/software/brm...