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Standard Deviation vs. Standard Error
  • n = sample size
  • Sigma (σ) = standard deviation
  • SEM = standard error of the mean
    • SEM = σ/√n
    • SEM < σ
    • SEM decreases as n increases
  • z-scores
    • 1 = +/- 1 σ around mean
    • = +/- 2 σ around mean
    • = +/- 3 σ around mean

 

Confidence Interval (CI)
  • Describes the range in which the mean would be expected to fall if the study were performed again and again
    • = range from [mean - Z(SEM)] to [mean + Z(SEM)]
    • 95% CI (alpha = 0.05) is standard 
      • for 95% CI, Z = 1.96
  • Outcomes 
    • if 0 falls within the CI when calculating the difference between 2 variables, H0 is not rejected and the result is not significant
    • if 1 falls within the CI when calculating OR or RR, H0 is not rejected and the result is not significant
T-test vs. ANOVA vs. χ2
  • T-test    
    • compares the means of 2 groups on a continuous variable  
  • ANOVA (analysis of variance)
    • compares the means of 3 or more groups on a continuous variable
  • χ2 ("chi-squared") 
    • tests whether 2 nominal variables are associated
    • used with 2x2 tables
      • e.g., effect of treatment on disease
Correlation Coefficient (r)
  • Pearson coefficient, r, is always between -1 and +1
  • Absolute value indicates strength of correlation between 2 variables 
  • Coefficient of determination = r2
Attributable Risk (AR)
  • AR is incidence in the exposed (Ie) - incidence in the unexposed (Iu) = Ie - Iu 
    • Ie = a/(a+b)
    • Iu = c/(c+d)
    • AR = a/(a+b) - c/(c+d)
  • The AR percent (ARP) is the attributable risk divided by incidence in the exposed (Ie)
    • ARP = 100* (Ie-Iu)/Ie = 100*[a/(a+b) - c/(c+d)]/[a/(a+b)]  
    • note that relative risk (RR) = Ie/Iu = a/(a+b) DIVIDED BY c/(c+d)
    • using math tricks
      • ARP = (RR-1)/RR 
 
 

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