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Sorting out statistical dilemmas P value or 95% CI

Sorting out statistical dilemmas P value or 95% CI. Dr. Jayaprakash Muliyil MD MPH DrPH Professor, Community Health Christian Medical College, Vellore. Fact vs theory. Inductive logic vs deductive logic. David Hume’s contention Karl Popper’s solution.

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Sorting out statistical dilemmas P value or 95% CI

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  1. Sorting out statistical dilemmasP value or 95% CI Dr. Jayaprakash Muliyil MD MPH DrPH Professor, Community Health Christian Medical College, Vellore

  2. Fact vs theory

  3. Inductive logic vs deductive logic

  4. David Hume’s contention • Karl Popper’s solution

  5. Probability of no disease given that the test is positive =1-ppv = 1- a/(a+b)

  6. Statistical tests of significance • Assumes null hypothesis is true • Provides p values • Is the probability of the observed difference occurring purely by chance. • P value is a function of sample size

  7. RR =2, P value >0.05 RR= 2, P value <0.05 RR =2, P value <0.001

  8. 95% Confidence Interval • Estimating the location of population parameter from sample statistic. • Frequency • Difference in frequency • Relative frequency (ratio)

  9. Normal curve

  10. Frequency • 95% of sample values will lie within 2 standard errors of the population parameter • Hence, when you create an interval of +- 2 standard errors around sample mean, 95% of the time, the population parameter will be included within it. • Higher the precision – narrower the interval

  11. Risk difference (difference in frequency) • Null value = 0 • If the risk difference confidence limits include 0 then the difference is not statistically significant

  12. Risk ratio • Null value =1 • If the risk ratio confidence interval includes 1 then the risk estimate is not statistically significant.

  13. Consider this OR =8 , 95% CI 2.87 to 21.21 OR =1.56 , 95% CI 1.05 to 2.29

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