Primer on statistical reporting and analyses for continuous variables Giuseppe Biondi Zoccai...
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Transcript of Primer on statistical reporting and analyses for continuous variables Giuseppe Biondi Zoccai...
Primer on statistical reporting and analyses
for continuous variablesGiuseppe Biondi Zoccai
University of Turin, Turin, Italy [email protected]
SCOPE OF THE PROBLEM
• Continuous variables are very common (e.g. age, left ventricular ejection fraction, hemoglobin concentration, hematocrit, late loss at angiographic analyses)
• Their reporting and analysis strongly depends on the underlying distribution (Gaussian [i.e. normal] versus non-Gaussian)
ALGORITHM
1. Check if variable is well known for having Gaussian distribution
a. If yes and sample size > 30 then proceed to point 2.b. If no or sample size < 30 then proceed to point 3.
2. Report variable as mean±standard deviation and compare it with Gossett-Student t test
ALGORITHM
3. Compare variable distribution with Gaussian distribution using one-sample Kolmogodorov-Smirnov test
a. If p>0.05 then go back to point 2.b. If p<0.05 then go back to point If no or sample size < 30
then proceed to point 4.
4. Report variable as median (1°-3° quartile) and compare it with Mann-Whitney U test (for indepent samples) or Wilcoxon rank-sum test (for related samples)
ALGORITHM
5. If instead than 2 groups, several groups are being compared, other tests should be employed, including ANOVA, MANOVA, or ANCOVA (after transformation) versus Kruskal-Wallis or Friedman non-parametric tests
KOLMOGODOROV-SMIRNOV TEST
KOLMOGODOROV-SMIRNOV TEST
KOLMOGODOROV-SMIRNOV TEST
GOSSETT-STUDENT T TEST
GOSSETT-STUDENT T TEST
GOSSETT-STUDENT T TEST
MANN-WHITNEY U TEST
MANN-WHITNEY U TEST
MANN-WHITNEY U TEST
Thank you for your attention
For any correspondence: [email protected]
For these and further slides on these topics feel free to visit the metcardio.org website:http://www.metcardio.org/slides.html