1 / 15

Understanding Statistical Dilemmas: P-values, Confidence Intervals, and Risk Ratios

This presentation by Dr. Jayaprakash Muliyil, Professor of Community Health at Christian Medical College, Vellore, discusses the challenges of interpreting statistical significance in health research. It elaborates on the concepts of p-values, confidence intervals, and risk ratios, exploring the differences between null hypotheses and statistical power. Dr. Muliyil highlights the implications of sample size on p-values and discusses practical examples of risk assessments, elucidating how to infer meaningful conclusions from statistical data in medical practice.

preston
Download Presentation

Understanding Statistical Dilemmas: P-values, Confidence Intervals, and Risk Ratios

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related