@NileshSKapoor @Thinkerks Indian doctors who have actually treated covid outpatients are smart enough & know that early rx works, unlike dghs bureaucrats who rarely see any patients and keep on making policies by just playing binary games with p-values
As pointed out in this article, the statistical community generally supports this idea.....
RT @AngelaReiersen: I think this article is very important: Scientists rise up against statistical significance https://t.co/QAUWLz18OO
Scientists rise up against statistical significance https://t.co/XHoMPvBc0X
Estão fazendo isso com a IVM e HCQ !
From the people I see arguing on Twitter, seems like large portions of scientists and physicians don't know these basic logical concepts. 👇🏻
Well, in here we love and need to be married with Statistics #EverlastingLove
RT @AngelaReiersen: I think this article is very important: Scientists rise up against statistical significance https://t.co/QAUWLz18OO
Many medical professionals are not adept at statistics. There should be a statistician or mathematician statement on all papers. Alpha and Beta error, statistical significance, null hypothesis definition and many very fundamental concepts are routinely wro
RT @AngelaReiersen: I think this article is very important: Scientists rise up against statistical significance https://t.co/QAUWLz18OO
RT @AngelaReiersen: I think this article is very important: Scientists rise up against statistical significance https://t.co/QAUWLz18OO
RT @AngelaReiersen: I think this article is very important: Scientists rise up against statistical significance https://t.co/QAUWLz18OO
RT @AngelaReiersen: I think this article is very important: Scientists rise up against statistical significance https://t.co/QAUWLz18OO
I think this article is very important: Scientists rise up against statistical significance https://t.co/QAUWLz18OO
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
Scientists rise up against statistical significance @Nature Link: https://t.co/FYIwL0E9pF
Scientists rise up against statistical significance https://t.co/ZyM9DbixUr
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
22 / Este artículo de Nature explica, entre otras cosas, la “falacia de la línea brillante” básica de confundir evidencia débil con eficacia con evidencia (fuerte) contra eficacia: https://t.co/dGvcXQlnQp
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
Scientists rise up against statistical significance https://t.co/9GxSTF1dIv
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
RT @Gusrocksan: https://t.co/F6O13PQdSE Probablemente el mejor paper que me ha enseñado @Geovann59684936 Gracias!!!
RT @Gusrocksan: https://t.co/F6O13PQdSE Probablemente el mejor paper que me ha enseñado @Geovann59684936 Gracias!!!
22/ このNatureの論文では、有効性を示す弱い証拠を、有効性を示さない(強い)証拠と勘違いするという基本的な「輝線の誤謬」について、特に説明している。 https://t.co/HGDNKAaE5a
RT @AbdenurFlavio: 22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for effica…
22/ This Nature paper explains among other things the basic “bright-line fallacy” of mistaking weak evidence for efficacy for (strong) evidence against efficacy: https://t.co/8DAoyrlpBH
savin 4 lates
@anastazze @Timeo_Danaos @Tipuncho Ah il y a "statistical significance". J'en parle pas mal et cet article résume la controverse pas trop mal. https://t.co/zDw9MMbNGi Tu peux aussi voir ces pages: https://t.co/JMKIKM5pqg
But what this essential boils down to, and what a magazine like Science should by now be aware of, is that findings should not be "hyped" based on a rhetorical device such as "statistical significance" known to be extremely flawed - abandon it! https://t.c
@AIBonthetwit @ShangoriGannos @AnsgarTOdinson @BretWeinstein It is critically important to contact science-friendly scientists in academia to get these people removed and/or retrained. https://t.co/tTgPQcTwvH And we do have an in; the NHST is broken, yet
@bdoody11 @pourover16 @BretWeinstein @mattyglesias So the Lopez-Medina RCT in JAMA is actually *weak evidence for (pretty strong) efficacy*, but is misinterpreted as *strong evidence against efficacy* due of the combination of (1) being underpowered with (
Hear, Hear!... Scientists rise up against statistical significance https://t.co/y6kCjmIVv8
Scientists rise up against statistical significance https://t.co/iRhkalTxzt
RT @JRamirezValles: “People will spend less time with statistical software, and more time thinking” @HEandB @PublicHealth @AcademiaObs…
A must read for young researchers. #ScienceTwitter Scientists rise up against statistical significance https://t.co/Gfjn8fEuWY #AcademicTwitter @AcademicChatter #phdchat
RT @JSchmukler: Me adelanto al próximo argumento del retardo: “no hicieron p porque se discute lanutilidad de p”. Correcto. Se discute. Per…
RT @JSchmukler: Me adelanto al próximo argumento del retardo: “no hicieron p porque se discute lanutilidad de p”. Correcto. Se discute. Per…
This link explains common error that happens all the time: people confuse underpowered but with intended effect as evidence against, whereas should be used as evidence for effect (even if weak evidence). https://t.co/ET0pEz4HLj
RT @AbdenurFlavio: @boulware_dr @julienpotet @BramanteCarolyn @mfpullenmd @StribJO @umnmedschool @UMNews If it turns out that some treatmen…
RT @JSchmukler: Me adelanto al próximo argumento del retardo: “no hicieron p porque se discute lanutilidad de p”. Correcto. Se discute. Per…
Brilhante!!!
RT @AbdenurFlavio: @boulware_dr @julienpotet @BramanteCarolyn @mfpullenmd @StribJO @umnmedschool @UMNews If it turns out that some treatmen…
RT @JSchmukler: Me adelanto al próximo argumento del retardo: “no hicieron p porque se discute lanutilidad de p”. Correcto. Se discute. Per…
@boulware_dr @julienpotet @BramanteCarolyn @mfpullenmd @StribJO @umnmedschool @UMNews If it turns out that some treatment groups achieve large measured relative reductions in hospitalization but with p>0.05 and are then interpreted as "no evidence", the
RT @JRamirezValles: “People will spend less time with statistical software, and more time thinking” @HEandB @PublicHealth @AcademiaObs…
Me adelanto al próximo argumento del retardo: “no hicieron p porque se discute lanutilidad de p”. Correcto. Se discute. Pero no se propone no hacer stats, sino ver los intervalos de confianza. Tenés los IC, Rodri? https://t.co/5Was6PzPeT
Claro. Pero nadie sugiere NO hacer análisis estadístico. No hay fondo para este pozo séptico eh. https://t.co/5Was6PzPeT
@OkCirujan Claro, mi punto es el concepto ´estadisticamente significativo´. Tests hay que aplicar siempre, pero no nos dice nada eso solo. Acá te paso ejemplo, pero si googleas p value y controversy veras cuan candente es el tema. https://t.co/1c61Hrw3EK
RT @JRamirezValles: “People will spend less time with statistical software, and more time thinking” @HEandB @PublicHealth @AcademiaObs…
“People will spend less time with statistical software, and more time thinking” @HEandB @PublicHealth @AcademiaObscura @Ass_Editors #stats @EPIDEMICpodcast #pvalue #biostatistics #scientist https://t.co/QvAjvFj8dm
@fenglich @statstwitbot https://t.co/zaVZMgtcKt This might be a good place to start... and the references would be good follow up. If you can’t access the articles you can reach out to the corresponding authors and ask them for a copy. There have also bee
RT @josh_totty: @dheansa_plastic Alternative take - the 24% RRR is clinically significant, justifies publication and is important in future…
@dheansa_plastic Alternative take - the 24% RRR is clinically significant, justifies publication and is important in future metaanalyses. Though P ≠ 0.05, the risk ratio estimate & 95%CI are somewhat compelling (see https://t.co/P6n7uh0XMV)
@usujason Here's an article you might be interested in, if you haven't read it already: https://t.co/YkXVXItt89
RT @TessNRoberts: @Jo_Lam_ I think the point is we should all be moving beyond p-value cut-offs as the sole criterion for interpreting stre…
@Jo_Lam_ I think the point is we should all be moving beyond p-value cut-offs as the sole criterion for interpreting strength of evidence https://t.co/VdPREdTvxj
Mentioned to the students today about the reproducibility crisis in Psychology - does anyone have a good piece written about it that I can send them? Something along the lines of this Nature article about p-values: https://t.co/vsJOMuWriG
RT @vamrhein: @naked_statist @Lester_Domes Strangely, whatever we write is often misunderstood as an attack on P-values, even if like in th…
@naked_statist @Lester_Domes Strangely, whatever we write is often misunderstood as an attack on P-values, even if like in the attached we explicitly say three times, on two printed pages of text, that we are NOT advocating any sort of "ban" on P-values ..
RT @AbdenurFlavio: @EliVieiraJr Randomizados pequenos demais para obter p<0.05 mesmo para um tratamento eficaz são ditos "underpowered". E…
@EliVieiraJr Randomizados pequenos demais para obter p<0.05 mesmo para um tratamento eficaz são ditos "underpowered". E o erro de interpretar como *negativos* estudos em que o grupo X se saiu empiricamente melhor do que placebo mas com p>0.05 é "brig
RT @TschoppLab: @_julien_roux Ours truly @vamrhein might be happy to join in... 😬 https://t.co/oiciASWTtf
@_julien_roux Ours truly @vamrhein might be happy to join in... 😬 https://t.co/oiciASWTtf
RT @AbdenurFlavio: @acsgomes @rimfo @schmittpaula @marcelofnalves Interpretar estudos nos quais o grupo de tratamento se saiu *melhor* do q…
@acsgomes @rimfo @schmittpaula @marcelofnalves Interpretar estudos nos quais o grupo de tratamento se saiu *melhor* do que o de placebo num desfecho X mas com p>0.05 como evidência *contra* eficácia é um exemplo grotesco de bright-line fallacy, muito be
@UlissesPSampaio @lebon80 @boulware_dr @filipe_rafaeli @joex92_ @JAMA_current A propos, here goes a reminder on the bright-line fallacy: https://t.co/8DAoyrlpBH
RT @GAMV65: Scientists rise up against statistical significance and make a call to use confidence intervals as compatibility intervals is…
And again this discussion...
RT @GAMV65: Scientists rise up against statistical significance and make a call to use confidence intervals as compatibility intervals is…
Scientists rise up against statistical significance and make a call to use confidence intervals as compatibility intervals is not a panacea what do you think ? @medel2021 @PolarBearby @pinabertoglia https://t.co/8gIT0PYQLD
RT @UlissesPSampaio: Everyone should read this before talking about "negative", "positive" trials and "p value". "Bureaucratic reasoning" l…
Everyone should read this before talking about "negative", "positive" trials and "p value". "Bureaucratic reasoning" leads to evidence being used in opposite direction of where it should.
RT @AbdenurFlavio: @HobbesMatraca @JAMA_current It's a prime example of bright-fallacy, made worse by interpreting weak evidence of strong…
@HobbesMatraca @JAMA_current It's a prime example of bright-fallacy, made worse by interpreting weak evidence of strong efficacy as strong evidence of lack of efficacy... it's absolutely depressing how much people do this https://t.co/8DAoyrlpBH
No idea what I'm talking about? 🤔 Here are a selection of recent articles: https://t.co/Gu9Sy7SSlT
@SD_Viz "the treatment group did better than the control group but p>0.05 so there's nothing to see here" is a prime example of the bright-line fallacy: https://t.co/8DAoyrlpBH