1 / 13

Calculating Statistical Significance and Confidence Intervals

Calculating Statistical Significance and Confidence Intervals. Bioterrorism Epidemiology Module 12 Missouri Department of Health And Senior Services. Tests of Significance (p values). Used to determine how likely it is that the observed results could have occurred by chance

melia
Download Presentation

Calculating Statistical Significance and Confidence Intervals

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. Calculating Statistical Significance and Confidence Intervals Bioterrorism Epidemiology Module 12 Missouri Department of Health And Senior Services

  2. Tests of Significance (p values) • Used to determine how likely it is that the observed results could have occurred by chance • Study population is a sample from a population • In the source population the amount of disease is the same for exposed and unexposed people

  3. Tests of Significance (p values) • This hypothesis is known as the null hypothesis • The minimum accepted p value for significance is 0.05 • The most frequently used significant test in epidemiology is the chi-square test

  4. Chi-Square (Χ2) (t-1) (ad-bc)2 (v1) (v0) (h1) (h0) Diseased Non-Diseased a b h1 Exposed c h0 d Non-Exposed v1v0 t

  5. Chi-Square (Χ2) Calculate the Chi-Square for this data and determine the p value from Table 8 Cases Controls 100 100 Exposed Non-Exposed 50 350

  6. Chi-Square (Χ2) (t-1) (ad-bc)2 (v1) (v0) (h1) (h0) Cases Controls Exposed 100 100 200 50 350 Non-Exposed 400 150 450 600 (599) (35,000-5,000)2 \ 5,400,000,000 = 99.83(p<.001)

  7. 95% Confidence Interval of an Odds Ratio and a Relative Risk There is a 95% likelihood that the true Risk Ratio falls between the lower and upper portion of the 95% confidence interval

  8. 95% CI for Relative Risk (RR) RR = (A/A+B) / (C/C+D) Upper 95% limit InRR = InRR+ 1.96 * SE(InRR) Lower 95% limit InRR = InRR- 1.96 * SE(InRR) Upper limit RR = e upper limit lnRR Lower limit RR = e lower limit lnRR Standard error of the natural log (RR) = (variance In)½ Variance of In = ((B/A) / (A+B)) + ((D/C) / (C+D)) DiseasedNot Diseased A B Exposed C D Non-Exposed

  9. Relative Risk Cohort Study Iexp = 10 / 1,000 X 100,000 = 1,000 per 100,000 Inexp = 5 / 3,000 X 100,000 = 167 per 100,000 RR = Iexp / Inexp = 1,000 / 167 = 6.00 DiseasedNon Diseased Exposed 10 990 Non-Exposed 5 2,995

  10. 95% CI for Relative Risk (RR) Upper 95% limit InRR = InRR+ 1.96 * SE(InRR) Lower 95% limit InRR = InRR- 1.96 * SE(InRR) Upper limit RR = e upper limit lnRR Lower limit RR = e lower limit lnRR Standard error of the normal log (RR) = (variance In)½ Variance of In (RR ) = ((B/A) / (A+B)) + ((D/C) / (C+D)) Upper 95% limit InRR = 1.79+ (1.96 * .547) = 2.86 Lower 95% limit InRR = 1.79– (1.96 * .547) = .72 Upper limit RR = e 2.86 = 17.46 Lower limit RR = e .72 = 2.05 Standard error of the normal log (RR) = (.299)½ = .547 Variance of In (RR) = 99 / 1000 + 599 / 3000 = .299 DiseasedNot Diseased 10 990 Exposed 5 2995 Non-Exposed

  11. 95% CI for Odds Ratio (OR) OR = (A/B) / (C/D) Upper limit InOR = InOR+ 1.96 * SE(InOR) Lower limit InOR = InOR- 1.96 * SE(InOR) Upper limit OR = e upper limit lnOR Lower limit OR = e lower limit lnOR Standard error of the natural log (OR) = (variance In)½ Variance of InOR =(1/A) + (1/B) + (1/C) + (1/D) CasesControls A B Exposed C D Non-Exposed

  12. Odds Ratios Case Control Study ODDS OF EXPOSUREcases = 100 / 50 = 2.0 ODDS OF EXPOSUREcontrols = 100 / 350 = 0.29 OR = ODDScases / ODDScontrols = 2 / 0.29 = 6.90 Cases Controls 100 100 Exposed Non-Exposed 50 350

  13. 95% CI for Odds Ratio (OR) Upper limit InOR = InOR+ 1.96 * SE(InOR) Lower limit InOR = InOR- 1.96 * SE(InOR) Upper limit OR = e upper limit lnOR Lower limit OR = e lower limit lnOR SE (lnOR) = (variance InOR)½ Variance of InOR =(1/A) + (1/B) + (1/C) + (1/D) Upper limit InOR = 1.93+(1.96 * .21) = 2.34 Lower limit InOR = 1.93– (1.96 * .21) = 1.52 Upper limit OR = e 2.34 = 10.38 Lower limit OR = e 1.52 = 4.57 SE (lnOR) = (.043)½ = .21 Variance of InOR =(.01) + (.01) + (.02) + (.003) = .043 Cases Controls 100 100 Exposed Non-Exposed 50 350

More Related