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Statistics don’t l ie – do people?

Statistics don’t l ie – do people?. Janez Stare Faculty of Medicine, Ljubljana. USA Today has come out with a new survey – apparently, three out of four people make up 75% of the population. David Letterman On the other hand It's amazing how authoritative you can sound

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Statistics don’t l ie – do people?

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  1. Statistics don’t lie–do people? Janez Stare Faculty of Medicine, Ljubljana

  2. USA Today has come out with a new survey – apparently, three out of four people make up 75% of the population. David Letterman On the other hand It's amazing how authoritative you can sound just by quoting some statistics ... And certainly Without data it is anyone’s opinion ... (In God we trust; all others must bring data.)

  3. So – statisticians don’t lie?

  4. A researcher viewed 107 publishedstudies comparing a new drug and a traditional therapy and found "studiesof new drugs sponsored by drug companies were more likely to favor those drugs than studies supported by noncommercial entities". In not a single case was a drug or treatment manufactured by the sponsoring company found inferior to another company's product.

  5. A typical lie • Cigarette manufacturer Lorillard claimed that "TRIUMPH BEATS MERIT" because "an amazing 60 percent said Triumph tastes as good or better than Merit.“ • Actually, 36 percent preferred Triumph, 24 percent said they were equal, and 40 percent preferred Merit.

  6. Phases of research • Planning • Collecting data • Data Analysis (together with description) • Interpretation of results We can ‘lie’ in every phase!

  7. Planning of research and data collection Example: 100 measurements on one sheet of paper 100 measurementson another sheet But – measurements are paired! Andthe guy doesn’t know how! When we plan our research, we must know what methods of analysis will be used!

  8. Missingdata! Example: duration of labour Two phases Measured variables: Duration of the first phasex1 Dur. of the second phasex2 Total durationx3 We got:

  9. Some lying graphs ‘Figures don’t lie, but liars can figure’ New York Times

  10. Washington Post

  11. What a fall!!

  12. Lower rang is better!!

  13. And some desperately bad graphs ?

  14. Analysis hospital n dead % dead 1 64 3 4,7 2 49 6 12,2 3 67 1 1,5 4 68 1 1,5 5 70 5 7,1 6 45 1 2,2 7 73 7 9,6 8 97 3 3,1 9 125 10 8,0 10 80 2 2,5 11 46 4 8,7 Does hospital 2 stand out? And what if hospitals are compared to some standard (say 5%)?

  15. PID-PAB ANALIZA COOP WONCA vprašalnik: SKUPNO: sešteti točke iz posameznih vprašanj (minimalno število je 6, maksimalno pa 30). Primerjati skupini s PAB in brez PAB glede na skupno število točk. ANALIZA Analizirati, kako posamezne spremenljivke vplivajo na kvaliteto življenja (COOP WONCA vprašalnik), tako na posamezne vidike kvalitete življenja kot na skupno oceno (seštevek točk). Analizirati ločeno za bolnike s PAB in ločeno za paciente brez PAB, ter za celo skupino pacientov skupaj. Analizirati vsaj: starost, spol, BMI, pas, sistolični in diastolični tlak, hemoglobin, s-glukoza, s-K, urea, kreatinin, CRP, celokupni holesterol, HDL, LDL, trigliceridi, u-proteini, u-glukoza, SCORE, minimalni GI, znižan GI min, aterosklerotična bolezen, angina pectoris, akutni koronarni sindrom, zožitev karotidne arterije,

  16. ishemični napad, možganska kap, intermitentna klavdikacija, klavdikacijska razdalja, ishemija uda, bolezni v družini, sladkorna bolezen, hipirlipidemije, arterijska hipertenzija, kajenje, razdražljivost, spanje, alkohol, sadje, zelenjava, zmerno gibanje, intenzivno gibanje, individualno svetovanje, skupinsko svetovanje, antiagregacijska terapija-skupaj, lipolitiki-skupaj, ACE in sartani-skupaj, antihipertenzivi, diuretiki, število zdravil-skupaj (to naj bo nova spremenljivka) The guy wanted 1114 tables with corresponding tests!

  17. Do the assumptions hold? 14 12 10 And something here 8 6 4 2 2 4 6 8 10 12 14 Something here

  18. When we need to know a bit more Example: Somebody was ‘explaining’ GDP for eleven years with sevenvariablesin a regression equation. He gotR2= 0,95. Wow! Bravo! But: The expected value of R2= 0,7 (under the null R2= 0)!!

  19. The famous 5 percent (or 1%) • Examples of reviews: • Please state that side effects were NOT different (p = 0.058). • Either something IS significantly different or IT IS NOT. • Please delete discussion of non-statistically significant results from the text. • Fisher • How much is 5%? • What is the difference between 5,1% and 4,9%?

  20. Interpretation of results 800 600 400 dead 200 New law 0 1990 1995 2000 2005 year

  21. Survival after AMI by sex

  22. Predicted survival by sex after controlling for age

  23. Relative survival of men and women

  24. There are no routine statistical questions, there are only questionable statistical routines • D.R. Cox

  25. don’t lie – people do. can’t lie – people can ! Statistics

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