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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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**Sorting out statistical dilemmasP value or 95% CI**Dr. Jayaprakash Muliyil MD MPH DrPH Professor, Community Health Christian Medical College, Vellore**David Hume’s contention**• Karl Popper’s solution**Probability of no disease given that the test is positive**=1-ppv = 1- a/(a+b)**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**RR =2, P value >0.05**RR= 2, P value <0.05 RR =2, P value <0.001**95% Confidence Interval**• Estimating the location of population parameter from sample statistic. • Frequency • Difference in frequency • Relative frequency (ratio)**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**Risk difference (difference in frequency)**• Null value = 0 • If the risk difference confidence limits include 0 then the difference is not statistically significant**Risk ratio**• Null value =1 • If the risk ratio confidence interval includes 1 then the risk estimate is not statistically significant.**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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