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#effectsize

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Dr Mircea Zloteanu ☀️ 🌊🌴<p>🚨New blog post 📝: Your Study Is Too Small (If You Care About Practically Significant Effects)</p><p><a href="https://mastodon.social/tags/effectsize" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>effectsize</span></a> <a href="https://mastodon.social/tags/precision" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>precision</span></a> <a href="https://mastodon.social/tags/poweranalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>poweranalysis</span></a> <a href="https://mastodon.social/tags/research" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>research</span></a> <a href="https://mastodon.social/tags/Psychology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Psychology</span></a> <a href="https://mastodon.social/tags/MCID" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MCID</span></a> <a href="https://mastodon.social/tags/SESOI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SESOI</span></a> <a href="https://mastodon.social/tags/samplesize" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>samplesize</span></a> </p><p> <a href="https://open.substack.com/pub/mzloteanu/p/your-study-is-too-small-if-you-care?r=3b457w&amp;utm_campaign=post&amp;utm_medium=web&amp;showWelcomeOnShare=true" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">open.substack.com/pub/mzlotean</span><span class="invisible">u/p/your-study-is-too-small-if-you-care?r=3b457w&amp;utm_campaign=post&amp;utm_medium=web&amp;showWelcomeOnShare=true</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statstab</span></a> #353 The Abuse of Power; The Pervasive Fallacy of Power Calculations for Data Analysis</p><p>Thoughts: An seminal paper on "post hoc" power calculations.</p><p><a href="https://mastodon.social/tags/power" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>power</span></a> <a href="https://mastodon.social/tags/QRPs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>QRPs</span></a> <a href="https://mastodon.social/tags/NHST" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>NHST</span></a> <a href="https://mastodon.social/tags/posthoc" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>posthoc</span></a> <a href="https://mastodon.social/tags/samplesize" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>samplesize</span></a> <a href="https://mastodon.social/tags/effectsize" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>effectsize</span></a></p><p><a href="https://www.tandfonline.com/doi/abs/10.1198/000313001300339897" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">tandfonline.com/doi/abs/10.119</span><span class="invisible">8/000313001300339897</span></a></p>
RDN<p>An overview of 67 different effect size estimators, including confidence intervals, for two-group comparisons:</p><p><a href="https://journals.sagepub.com/doi/full/10.1177/25152459251323186" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">journals.sagepub.com/doi/full/</span><span class="invisible">10.1177/25152459251323186</span></a></p><p>The authors have also developed a Shiny web app to evaluate these.</p><p><a href="https://floss.social/tags/Science" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Science</span></a> <a href="https://floss.social/tags/Statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Statistics</span></a> <a href="https://floss.social/tags/EffectSize" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>EffectSize</span></a> <a href="https://floss.social/tags/RStats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RStats</span></a></p>
Bjørn Sætrevik<p>It always takes me some minutes to look up the interpretation guidelines for various effect size measures (yes, I know the rules of thumb are somewhat arbitrary). Today I edited Wikipedia to show three different guidelines for four different measures in the same table. Hopefully this can save some time for other researchers. </p><p><a href="https://fediscience.org/tags/methodology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>methodology</span></a> <a href="https://fediscience.org/tags/psychometrics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>psychometrics</span></a> <a href="https://fediscience.org/tags/EffectSize" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>EffectSize</span></a> <a href="https://fediscience.org/tags/OpenScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenScience</span></a> <a href="https://fediscience.org/tags/wikipedia" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>wikipedia</span></a></p>
Unpartitioned Variance 50% off<p><a href="https://c.im/tags/malcolmGladwell" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>malcolmGladwell</span></a> has another book, I guess trying to rescue his much-nitpicked <a href="https://c.im/tags/TippingPoint" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>TippingPoint</span></a>.</p><p>IDK if he's a net positive force in the world or not. As a <a href="https://c.im/tags/psychologist" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>psychologist</span></a> I've occasionally looked up the original <a href="https://c.im/tags/research" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>research</span></a> he cites. He tends to portray findings in black-and-white terms, like "People do X in Y situation!" when, most often, I've found the research best supports something like "In some studies 12% of people did X in Y situation despite previous <a href="https://c.im/tags/models" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>models</span></a> predicting it should only be 7%" or "The mean of the P group was 0.3 standard deviations higher than the mean of the Q group".</p><p>I see many of his grand arguments as built more or less on a house of cards. Or rather, built on a house of semi-firm jell-o that he treats as if it were solid bricks.</p><p>I'm not knocking (most of) the <a href="https://c.im/tags/behavioralScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>behavioralScience</span></a> he cites; Hell, I'm a behavioral scientist and I think this meta-field has a ton to offer. I just think it's important to keep <a href="https://c.im/tags/EffectSize" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>EffectSize</span></a> and <a href="https://c.im/tags/PracticalSignificance" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PracticalSignificance</span></a> built into any more complex theories or models that rely on the relevant research instead of assuming that <a href="https://c.im/tags/StatisticalSignificance" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>StatisticalSignificance</span></a> means "Everything at 100%". I'm sure there's some concise way to say this. </p><p>Overall, I think he plays fast and loose with a lot of scientific facts, stacking them up as if they were all Absolutely Yes when they're actually Kinda Maybe or Probably Sort Of and I don't think the weight of the stack can be borne by the accumulated uncertainty and partial applicability indicated by the component research.</p><p>So I take everything he says with huge grains of salt and sometimes grimaces, even though I think sometimes he identifies really interesting perspectives or trends.</p><p>But is it overall good to have someone presenting behavioral research, heavily oversimplified to fit the author's pet theory? It gets behavioral science in the public eye. It helps many people with no connection to behavioral science understand the potential usefulness and perhaps scale of the fields. It also sets everyone--especially behavioral scientists--up for a fall. It's only a matter of time after each of his books before people who understand the research far better than he does show up to try to set the record straight, and then what has happened to public confidence in behavioral science?</p><p>Meh.</p><p><a href="https://c.im/tags/statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statistics</span></a> <a href="https://c.im/tags/data" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>data</span></a> <a href="https://c.im/tags/competence" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>competence</span></a></p>