Odds Ratios_default

The video provides a brief introduction to odds ratios in research.
Focuses on the definition, interpretation, and associated terminology of odds ratios.
Not intended as a tutorial on how to calculate odds ratios.

Odds Ratio (OR): A measure of association between an exposure and an outcome.
- Quantifies the relationship between an independent variable (exposure) and a dependent variable (outcome).
- Indicates how much higher the odds of exposure are in one group compared to another.
Groups involved in an analysis can vary based on the research design, which may involve:
- Between groups design (two separate groups).
- Different conditions of an independent variable.
- Any dichotomous specifications used by researchers.

Important to differentiate between odds and risk:
- Odds: Used in the calculation of odds ratios.
- Risk: Used in calculating relative risk.
Ensure language used when reporting results matches the type of analysis performed by researchers.

Interpretation Guidelines:
- An odds ratio of 1.0: No association between exposure and outcome.
  - Odds of exposure in one group is the same as in another group (reference group).
- An odds ratio greater than 1: Indicates a potential risk factor.
  - Example: OR of 1.5 means a 50% increase in the odds of the outcome due to exposure.
- An odds ratio less than 1: Indicates a protective factor against the outcome.
  - Example: OR of 0.3 means a 30% decrease in the odds of an outcome with the given exposure.
The further the odds ratio is from 1, the stronger the association.
P-value: Indicates statistical significance.
- An odds ratio is statistically significant if its p-value is less than 0.05.

Confidence Interval (CI): Reported with odds ratios, gives a range of potential true odds ratios for the larger population.
- Example: OR of 2.4 presented with CI of (1.9, 4.3) means the true OR likely falls between these two numbers.
Evaluate the confidence interval:
- If the CI includes 1, the result is not statistically significant (indicates no association).
- Statistically significant if both limits are greater than 1 or both are less than 1.

Adjusted Odds Ratios (AOR): Take into account confounding variables that may affect the relationship.
- Useful in complex real-life situations where other variables might influence outcomes.
- Control for these confounders to measure the direct association between exposure and outcome.

Overview of odds ratios, interpretation, and associated terminology aimed at enhancing understanding for reading research articles.
Encouragement to ask questions on course forums for better clarification of material.