How To Conduct Statistical Analysis in Research

EXAMPLES OF STATISTICS USE IN SPECIFIC STUDIES:

• Measurements will represent characteristics of entire populations

• Measures a disease in relation to a variable of interest

• Correlation coefficient quantifies the linear relationship between the exposure of interest or “predictor” and the disease or “outcome” being studied

  • Examples: Pearson’s “r”; Spearman’s “T”; or Kendall’s “K”

• Value of the coefficient is between +1 and -1

• Positive 1 = perfect correlation where as the predictor increases, the outcome (or risk of outcome) increases

• Negative 1 = perfect inverse correlation where as the predictor increases the outcome (or risk of outcome) decreases

Observational Analytic Studies:

• Researchers record participants’ exposures and outcomes

• Two types: Case-control and Cohort

  • Case-control:

    • Participants are chosen based on whether they do (cases) or do not (controls) have the disease of interest

    • The cases and controls are then compared as to whether or not they have the exposure of interest

    • The difference in the prevalence of exposure between the disease/no disease groups can be tested using the odds ratio

    • Odds ratio (see above)

    • Then, determine the significance of your results by finding the confidence interval

  • Cohort Study:

    • Observation of a group of participants over a period of time during which outcomes develop

    • Retrospective or prospective

      • Retrospective

        • All pertinent events (both exposure and disease) have already occurred at the time the study has begun

        • The study investigators rely on previously collected data on exposure and disease

      • Prospective

        • The disease/outcome has not yet occurred

        • Study investigator must follow participants into the future to assess any difference in the incidence of the disease/outcome between the types of exposure

        • The incidence of the disease/outcome is compared between the exposed and unexposed groups using a relative risk (RR) calculation

Resources:

• CDC. Principles of Epidemiology. Centers for Disease Control and Prevention. Published 2019.

• Curtis AE, Smith TA, Ziganshin BA, Elefteriades JA. The Mystery of the Z-Score. AORTA, August 2016, Volume 4, Issue 4:124-130.

• Government of Canada SC. 4.5 measures of Dispersion 4.5.3 calculating the variance and standard deviation. 4.5.3 Calculating the variance and standard deviation. Published September 2, 2021. Accessed November 24, 2022. https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch12/5214891-eng.htm.

• Krousel-Wood MA, Chambers RB, Muntner P. Clinicians’ Guide to Statistics for Medical Practice and Research: Part I. Ochsner J. 2006 Winter; 6(2): 68–83.