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Logical thinking in scientifc work and most frequent errors from idea to publication Prof. dr. sc. Mladen Petrovečki Ph.D. Postgraduate Study Zagreb University School of Medicine 2007/08

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1. Typing error from idea to publication Prof. dr. sc. Mladen Petrovečki Ph.D. Postgraduate Study Zagreb University School of Medicine 2007/08 Logical thinking in scientific work and most frequent errors

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2. Logic, reasoning www.glasbergen.com/

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Logic of scientific work Mirko Jakić. Logika. Školska knjiga, Zagreb 2003. 1.rules of logic and logic itself as a way of valid thinking is more expressed in science and philosophy compared to other human activities… 2.science is recognized by utilizing empirical methods and therefore logic is prerequisite in scientific methodology...

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3.use of is logic evident in using logical reasoning, by using terms such as rules, conclusions, definitions, distributions, proves, etc. 4.logic – how our thinking is valid in our mission to find the truth… Logic of scientific work

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Logic of “scientific” work

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Types of logic www.cartoonstock.com

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3. Unscientific procedures diligence (habit, attitude, manner, believe, momentum) authority intuition

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More unscientific procedures

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4. Argument, proof

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5. Research logic system models of the system deterministic probabilistic event probability p(E) 0 p(E) 1

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6. Probability Machiavelli za početnike. Jesenki & Turk, Zagreb

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Probability, a term mathematical calculation that something, event, will occur mathematic probability theory statistics mathematics scientific methodology logic, philosophy reasoning about event feasibleness

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Probability, calculation symbol – P No. of expected events P = No. of all events values range 0 – 1: 0 – impossible event 1 – certain event

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Probability vs. fortune

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www.cartoonstock.com Probability vs. fortune II

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Probability vs. coincidence

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www.christianforums.com/ Probability vs. impossibility

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Probability, the term probability vjerojatnost, mogućnost possibility mogućnost, vjerojatnost, izvedivost likelihood vjerojatnost, mogućnost chance mogućnost, prigoda, slučaj, slučajnost, vjerojatnost, sreća, povoljna prilika odds izgled, prednost, vjerojatnost, slučajnost

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probability calculation probabilistic model of the system 7. Statistics

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Lord Kelvin (1824.-1907.) James C. Maxwell (1831.-79.) Ludwig Boltzmann (1844.-1906.) Willard Gibbs (1839.-1903.) p = ? Statistical mechanics

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Statistical asimmetry 10A : 10B 180.000 combinations p = 5,56x10 -6

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1 : 180.000 Statistical mechanics

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Second low of thermodynamics closed system: entropy const. entropy disorder (chaos) in closed system is constant or A. Šiber: Red i nered http://eskola.hfd.hr/clanci/entropija/entropija_ as.html

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population variable knowledge about population ... 8. Measuring & 9. Research

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10. Variable all variables in research as many of them the end of research simple complex (data) accuracy (numbers) measuring scales

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11. Measuring scales RATIO ORDINAL NOMINAL INTERVAL

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12. Error systematic incidental

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13. Population populationvariable samplestatistical data analysis knowledge on population SAMPLING knowlede on sample

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14. Sample part of population what? who? when? where? size

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Sample representative able to be measured probabilistic simple system stratified cluster

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Sample unrelated related

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15. Sampling www.statehousereport.com

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Sampling MedCalc

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16. Bias (sampling)

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Bias – systemic sampling error prevalence bias (Neyman) admittance rate bias (Berkson) answering rate bias etc. Bias (sampling)

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17. Blinding single-blind double-blind triple-blind quadruple-blind

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Bias, blinding

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18. Control must have to be compared with experimental group Hawthorn effect research with no control group subject changes behavior with a knowledge that is a part of experiment subject feels better with knowledge to be a part of experiment

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19. Hypothesis http://nhcs.k12.in.us/nhe/sciencefair/

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20. Statistical hypothesis uelemental statement utruth or not (false, lie) uhypothesis testing finding the truth Ivana Brlić Mažuranić Kako je Potjeh tražio istinu Mladost, Zagreb; Albert Kinert, 1967.

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Statistical hypothesis utruth real object state probabilistic system: truth probability usignificant any occasion other that accidentally: probability level of significance

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21. Null-hypothesis No difference

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22. Testing the hypothesis A.null-hypothesis B.statistical test C.level of significance D.statistics calculation E.conclusion

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A. Hypothesis null – H 0 – no difference alternate – H 1 – difference exists only one can be truthful only one can be accepted, other will be rejected

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B. Choosing the test measuring scales sample size related on unrelated samples data distribution parametric nonparametric no. of variables etc.

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23. Statistical tests ScaleOne sampleTwoThree or more relatedunrelatedrelatedunrelated NominalbinomialMcNemarCohran chi-squareFisherchi-sqr. chi-square/ OrdinalKol.-Smirn.WilcoxonFriedman MWp/median MosesKW Interval... Ratio...

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Paired & unpaired tests

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C. Level of significance P if defined before statistics – probability of rejecting H 0 when H 0 = is truth -error (type I error or false positive error) as less as possible default values, e.g. P<0,05

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24. Statistical errors

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D. Statistics computation... P = exact value three decimals P > 0,05

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25. Software

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26. Concluding (E) low P low possibility to reject the truth conclusion: P < low probability that H 0 is true reject (not accept) null hypothesis accept alternate hypothesis statement “...” is truth with P =...

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27. Yes & No in statistics hypothesis = ? calculation = ? correct data = ? all conditions for statistic valid = ? no limitations = ?

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Example 1: “not” in correlation x y x y x y

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Nrp linear 1180,250,006 logarithm1180,43<0,001 Example 1, cont.

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lecturesstudentsstudents qualityZagrebother well10 31 bad 0 19 total1050 Example 2: “not” with 2 -test

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Lupus 2004;14:426 Example 3: another “not”

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ne valja / valja Lancet 2007;370:1490 Example 4: “not” in graphs

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28. E-help

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29. Significance vs. accuracy www.mathworks.com

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30. The truth

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Literature Marušić M., ed. Principles of Research in Medicine 1st ed. in English Zagreb Medicinska naklada, 2008.

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Prof. dr. Mladen Petrovečki Katedra za medicinsku informatiku Medicinski fakultet Sveučilišta u Rijeci http://mi.medri.hr Odjel za imunološke pretrage Klinički zavod za laboratorijsku dijagnostiku Klinička bolnica “Dubrava”, Zagreb www.kbd.hr/lab mp@kbd.hrmp@kbd.hr

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