Please confirm topic selection

Are you sure you want to trigger topic in your Anconeus AI algorithm?

Please confirm action

You are done for today with this topic.

Would you like to start learning session with this topic items scheduled for future?

Updated: Oct 6 2022

Statistical Measures

Images
https://upload.medbullets.com/topic/101012/images/standard-deviation.jpg
https://upload.medbullets.com/topic/101012/images/untitled-1.jpg
  • 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 = +/- 2 σ around mean
      • 3 = +/- 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
    • Significance
      • statistical significance refers to whether p < 0.05
      • clinical significance requires that a statistically significant result be also clinically meaningful
  • 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
  • Regression Analysis
    • Regression analysis allows for the an outcome variable to be estimated from various predictor variables while adjusting for covariates
      • Linear regression
        • Outcome variable is continuous
        • Predictor variables can be continuous or categorical
      • Logistic regression
        • Outcome variable is binary
        • Predictor variables can be continuous or categorical
        • Exponentiation of the coefficients yields the odds ratio for that predictor
Card
1 of 0
Question
1 of 14
Private Note