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

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Presentation on theme: "Statistics don’t lie – do people? Janez Stare Faculty of Medicine, Ljubljana."— Presentation transcript:

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.) 2

3 So – statisticians don’t lie? 3

4 A researcher viewed 107 published studies comparing a new drug and a traditional therapy and found "studies of 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. 4

5 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. A typical lie 5

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

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

8 Missing data! Example: duration of labour Two phases Measured variables: Duration of the first phase x 1 Dur. of the second phase x 2 Total duration x 3 We got: 8

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

10 Washington Post 10

11 11

12 What a fall!! 12

13 Lower rang is better!! 13

14 And some desperately bad graphs ? 14

15 hospital ndead% dead 164 3 4,7 249 6 12,2 367 1 1,5 468 1 1,5 570 5 7,1 645 1 2,2 773 7 9,6 897 3 3,1 9 125 10 8,0 1080 2 2,5 1146 4 8,7 Analysis Does hospital 2 stand out? And what if hospitals are compared to some standard (say 5%)? 15

16 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

17 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

18 2468101214 2 4 6 8 10 12 14 Something here And something here Do the assumptions hold? 18

19 When we need to know a bit more Example: Somebody was ‘explaining’ GDP for eleven years with seven variables in a regression equation. He got R 2 = 0,95. Wow! Bravo! But: The expected value of R 2 = 0,7 (under the null R 2 = 0)!! 19

20 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

21 1990199520002005 0 200 400 600 800 year dead New law Interpretation of results 21

22 Survival after AMI by sex 22

23 Predicted survival by sex after controlling for age 23

24 Relative survival of men and women 24

25 There are no routine statistical questions, there are only questionable statistical routines D.R. Cox 25

26 Statistics !can’t lie – people can don’t lie – people do. 26

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