Publications by Daniel Lakens
Power analysis for default Bayesian t-tests
One important benefit of Bayesian statistics is that you can provide relative support for the null hypothesis. When the null hypothesis is true, p-values will forever randomly wander between 0 and 1, but a Bayes factor has consistency (Rouder, Speckman, Sun, Morey, & Iverson, 2009), which means that as the sample size increases, the Bayes Factor ...
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The correlation between original and replication effect sizes might be spurious
In the reproducibility project, original effect sizes correlated r=0.51 with the effect sizes of replications. Some researchers find this hopeful.Less-popularised findings from the “estimating the reproducibility” paper @Eli_Finkel #SPSP2016 pic.twitter.com/8CFJMbRhi8— Jessie Sun (@JessieSunPsych) January 28, 2016 I don’t think we should ...
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The correlation between original and replication effect sizes might be spurious
In the reproducibility project, original effect sizes correlated r=0.51 with the effect sizes of replications. Some researchers find this hopeful.Less-popularised findings from the “estimating the reproducibility” paper @Eli_Finkel #SPSP2016 pic.twitter.com/8CFJMbRhi8— Jessie Sun (@JessieSunPsych) January 28, 2016 I don’t think we should ...
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The difference between a confidence interval and a capture percentage
I was reworking a lecture on confidence intervals I’ll be teaching, when I came across a perfect real life example of a common error people make when interpreting confidence intervals. I hope everyone (Harvard Professors, Science editors, my bachelor students) will benefit from a clear explanation of this misinterpretation of confidence interv...
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One-sided F-tests and halving p-values
After my previous post about one-sided tests, some people wondered about two-sided F-tests. And then Dr R recently tweeted: No, there is no such thing as a one-tailed p-value for an F-test. reported F(1,40)=3.72, p=.03; correct p=.06 use t-test for one-tailed.— R-Index (@R__INDEX) April 5, 2016 I thought it would be useful to illustrate 1) why...
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One-sided F-tests and halving p-values
After my previous post about one-sided tests, some people wondered about two-sided F-tests. And then Dr R recently tweeted: No, there is no such thing as a one-tailed p-value for an F-test. reported F(1,40)=3.72, p=.03; correct p=.06 use t-test for one-tailed.— R-Index (@R__INDEX) April 5, 2016 I thought it would be useful to illustrate 1) why...
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Absence of evidence is not evidence of absence: Testing for equivalence
See the follow up post where I introduce my R package and spreadsheet TOSTER to perform TOST equivalence tests, and link to a practical primer on this topic. When you find p > 0.05, you did not observe surprising data, assuming there is no true effect. You can often read in the literature how p > 0.05 is interpreted as ‘no effect’ but due t...
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Absence of evidence is not evidence of absence: Testing for equivalence
When you find p > 0.05, you did not observe surprising data, assuming there is no true effect. You can often read in the literature how p > 0.05 is interpreted as ‘no effect’ but due to a lack of power the data might not be surprising if there was an effect. In this blog I’ll explain how to test for equivalence, or the lack of a meaningful ...
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Dance of the Bayes factors
You might have seen the ‘Dance of the p-values’ video by Geoff Cumming (if not, watch it here). Because p-values and the default Bayes factors (Rouder, Speckman, Sun, Morey, & Iverson, 2009) are both calculated directly from t-values and sample sizes, we might expect there is also a Dance of the Bayes factors. And indeed, there is. Bayes fact...
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