Statistics don’t l ie – do people?
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Statistics don’t lie – do people? Janez Stare Faculty of Medicine, Ljubljana
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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 - PowerPoint PPT Presentation
Transcript of Statistics don’t l ie – do people?
Statistics don’t lie – do people?
Janez StareFaculty 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 soundjust by quoting some statistics ...
And certainly
Without data it is anyone’s opinion ...(In God we trust; all others must bring data.)
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So – statisticians don’t lie?
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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.
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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
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Phases of research
• Planning• Collecting data• Data Analysis (together with description)• Interpretation of results
We can ‘lie’ in every phase!
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Planning of research and data collection
Example:100 measurements on one sheet of paper100 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!
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Missing data!
Example: duration of labourTwo phasesMeasured variables:Duration of the first phase x1
Dur. of the second phase x2
Total duration x3
We got: !!! 31 xx
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Some lying graphs
New York Times
‘Figures don’t lie, but liars can figure’
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Washington Post
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What a fall!!
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Lower rang is better!!
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And some desperately bad graphs
?
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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
Analysis
Does hospital 2 stand out?
And what if hospitals are compared to some standard (say 5%)?
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PID-PAB ANALIZA
COOP WONCA vprašalnik:
SKUPNO: sešteti točke iz posameznih vprašanj (minimalno številoje 6, maksimalno pa 30). Primerjati skupini s PAB in brez PAB gledena skupno število točk.
ANALIZA
Analizirati, kako posamezne spremenljivke vplivajo na kvalitetoživljenja (COOP WONCA vprašalnik), tako na posamezne vidikekvalitete življenja kot na skupno oceno (seštevek točk).Analizirati ločeno za bolnike s PAB in ločeno za paciente brezPAB, ter za celo skupino pacientov skupaj. Analizirati vsaj:starost, spol, BMI, pas, sistolični in diastolični tlak,hemoglobin, s-glukoza, s-K, urea, kreatinin, CRP, celokupniholesterol, HDL, LDL, trigliceridi, u-proteini, u-glukoza, SCORE,minimalni GI, znižan GI min, aterosklerotična bolezen, anginapectoris, akutni koronarni sindrom, zožitev karotidne arterije,
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ishemični napad, možganska kap, intermitentna klavdikacija,klavdikacijska razdalja, ishemija uda, bolezni v družini, sladkornabolezen, hipirlipidemije, arterijska hipertenzija, kajenje,razdražljivost, spanje, alkohol, sadje, zelenjava, zmerno gibanje,intenzivno gibanje, individualno svetovanje, skupinsko svetovanje,antiagregacijska terapija-skupaj, lipolitiki-skupaj, ACE insartani-skupaj, antihipertenzivi, diuretiki, številozdravil-skupaj (to naj bo nova spremenljivka)
The guy wanted 1114 tables with corresponding tests!
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2 4 6 8 10 12 14
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68
1012
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Something here
And
som
ethi
ng h
ere
Do the assumptions hold?
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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 R2 = 0,95.
Wow! Bravo!But:The expected value of R2 = 0,7 (under the null R2 = 0)!!
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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%?
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1990 1995 2000 2005
020
040
060
080
0
year
dead
New law
Interpretation of results
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Years
Sur
viva
l Pro
babi
lity
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
0.0
0.2
0.4
0.6
0.8
1.0
men
women
Survival after AMI by sex
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Years
Sur
viva
l Pro
babi
lity
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
0.0
0.2
0.4
0.6
0.8
1.0
men
women
Adjusted to: age=61
Predicted survival by sex after controlling for age
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Relative survival of men and women
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There are no routine statistical questions, there are only questionable statistical routines
D.R. Cox
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Statistics !can’t lie – people candon’t lie – people do.
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