#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
#pvalues
#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
https://discourse.datamethods.org/t/significance-tests-p-values-and-falsificationism/4738
#statstab #384 When to use Fisher versus Neyman-Pearson framework?
Thoughts: 13y old post, still a good read today. Uni season is almost upon us, so it's good to learn this stuff.
#NHST #pvalues #RAFisher #NeymanPearson #Fisher #forum
#statsexchange
https://stats.stackexchange.com/questions/23142/when-to-use-fisher-versus-neyman-pearson-framework
In grad school I noticed a printed message on the wall of our research lab. It was something like "distill information from the hint of implication" (bad memory).
I innocently said to an older grad student, "Yeah, that does sound like a way to commit Type-I errors" or something equivalent.
Well, that's not what the older grad student took from the sign and I got a very cold, slightly huffy response.
#statistics #probability #pvalues #typeIerror #sample #population
#statstab #359 A Pragmatic Approach to Statistical Testing and Estimation (PASTE)
Thought: A (basic) guide to some alternatives to p-values: bayesian posterior intervals, Bayes Factors, and AIC.
How to cheat at settlers by loading the dice (2017)
#HackerNews #cheat #settlers #settlersofcatan #loadingdice #gamingstrategy #pvalues
@lakens Your discussion of #pvalues is really a bit odd. "Just calculate a number that has no real interpretation, and then interpret it cautiously."* That's bogus.
Importantly, you missed the opportunity to making the point that, relatively, your p-values do have an interpretation: If you order your effects by p-value from low to high, the top of this list contains better candidates for a future study than the bottom.
*these are my words paraphrasing/interpreting Daniel Lakens
#statstab #337 Confidence intervals and tests are two sides of the same research question
Thoughts: Comment describing the connection between NHST p-values/test and Confidence Intervals (CI).
#NHST #ConfidenceIntervals #pvalues #frequentist #estimation
#statstab #309 The statistical significance filter leads to overoptimistic expectations of replicability
Thoughts: Not sure how many researchers interpret p-values are indexes of replicability, but they shouldn't.
#statstab #300 (!!!) 🥳🎉
Beyond the forest plot: The drapery plot
Thoughts: I can't believe they didn't call these 'tepee plots'.
I think they are cluttered, but can be useful.
#metaanalysis #pvalues #consonancecurve #pvaluefunction #dataviz #prediction #plots #figures #R
#statstab #298 Replication: Do not trust your p-value, be it small or large
Thoughts: Even under exact replications, a p-values is not very good at predicting the p-value in a future study. p=.05 ~ 50% rep.
#statstab #295 The Fallacy of the Null-Hypothesis Significance Test
Thoughts: "the [..] aim of a scientific experiment is not to precipitate decisions, but to make an appropriate adjustment in the degree to which one accepts, or believes, the hypothesis"
#NHST #Bayes #ConfidenceIntervals #pvalues #significance #testing #hypotheses #likelihood #critique #fallacy
#statstab #289 The meaning of significance in data testing
Thoughts: Fisherian significance testing =/= Neyman-Pearson statistical hypothesis testing. Many debates on p-values and frequentist stats are due to this confusion.
#statstab #287 Dance of the p Values
Thoughts: One of my go-to demonstrations for the variability of p-values, and why they say so little about a study.
#pvalues #NHST #education #estimation #frequentist #replication #error #visualization #teaching
#statstab #272 Different meanings of p-values
Thoughts: A riveting (& confusing) discussion on the definitions & properties of p-values. W/ guest appearance from some big names in stats, from all camps.
"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."
Longford (2005) http://www.stat.columbia.edu/~gelman/stuff_for_blog/longford.pdf
#modeling #nullHypothesis #probability #probabilities #pValues #statistics #stats #statisticalLiteracy #bias #inference #modelling #regression #linearRegression
#statstab #234 Not all alphas can be justified
Thoughts: When using discrete distributions, with few outcomes, your alpha cannot always take the values you want. Same with the distribution of p-values under the null.
Surveys, coincidences, statistical significance 🧵
"What Educated Citizens Should Know About Statistics and Probability"
By Jessica Utts, in 2003: https://ics.uci.edu/~jutts/AmerStat2003.pdf via @hrefna
#nullHypothesis #probability #probabilities #pValues #statistics #stats #education #higherEd #statisticalLiteracy #bias #media #causalInference
#statstab #217 The distribution of p-values obtained in replications depends only on the original p-value. How can it be true?
Thoughts: A great discussion where the author @thenewstats chimes in to explain the issue.
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