Podcast
Questions and Answers
What is the purpose of the 'comparison' in the final proof process?
What is the purpose of the 'comparison' in the final proof process?
- To measure the extent of association, effect, or risk (correct)
- To establish a cause and effect relationship
- To determine if the study methods are accurate
- To suggest additional studies using large sample sizes
What is the significance of Step 1 in establishing an 'exposure - outcome' relationship?
What is the significance of Step 1 in establishing an 'exposure - outcome' relationship?
- Conducting hypothesis testing
- Determining statistical significance
- Ensuring the accuracy of study results and avoiding spurious findings (correct)
- Evaluating indirect relationships with confounders
If a study has a non-significant p-value, what is one possible reason ?
If a study has a non-significant p-value, what is one possible reason ?
- Inclusion of strong confounders
- Low power of the study (small sample size) (correct)
- High power of the study
- Overestimation of the study results
What should an investigator consider if the 'exposure - outcome' association is statistically significant?
What should an investigator consider if the 'exposure - outcome' association is statistically significant?
What is suggested if the exposure-outcome association is not statistically significant?
What is suggested if the exposure-outcome association is not statistically significant?
'Validity, reliability, and bias' are factors considered in which step of establishing an exposure - outcome relationship?
'Validity, reliability, and bias' are factors considered in which step of establishing an exposure - outcome relationship?
Which type of association is exemplified by the relationship between shoe size and reading performance in elementary school children?
Which type of association is exemplified by the relationship between shoe size and reading performance in elementary school children?
What is the main purpose of a 'comparison' in observational studies when evaluating associations?
What is the main purpose of a 'comparison' in observational studies when evaluating associations?
In the context of epidemiological studies, what does it mean when we hypothesize that a factor 'may have a role in etiology'?
In the context of epidemiological studies, what does it mean when we hypothesize that a factor 'may have a role in etiology'?
Which statistical measures are commonly used as the extent of 'Association' or 'Effect' in observational studies?
Which statistical measures are commonly used as the extent of 'Association' or 'Effect' in observational studies?
When evaluating a potential causal relationship between two factors in epidemiology, what should be emphasized before drawing conclusions?
When evaluating a potential causal relationship between two factors in epidemiology, what should be emphasized before drawing conclusions?
What is the first question that must be asked when an association is observed?
What is the first question that must be asked when an association is observed?
How is bias defined in the context of a study?
How is bias defined in the context of a study?
Why is bias considered a systematic error?
Why is bias considered a systematic error?
What is the impact of bias on the estimate of an exposure's effect?
What is the impact of bias on the estimate of an exposure's effect?
How do alternative explanations like bias and confounding affect study results?
How do alternative explanations like bias and confounding affect study results?
When observing an association, what might bias or confounding lead researchers to falsely conclude?
When observing an association, what might bias or confounding lead researchers to falsely conclude?
Study Notes
Bias and Confounding
- Bias is a systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure's effect on the risk of disease.
- Bias can produce spurious results, leading to conclusions of a valid statistical association when none exists or vice versa.
- The effect of bias will be an estimate either above or below the true value.
Establishing a Cause & Effect Relationship
- The process of establishing a cause & effect relationship involves a sequence of steps.
- Step 1: Ensure the results of the study are accurate and not spurious, considering correct methods, validity, reliability, and bias.
- Step 2a: Determine if statistical results indicate an association, using p-value and 95% CI.
- Step 2b: If not significant, consider the possibility of low power due to a small sample size, and suggest additional studies or meta-analysis.
- Step 3: Evaluate if the relationship is due to an indirect relationship with a third variable (confounder).
- Step 4: If the confounder is excluded, test the postulated causal relationship on the criteria of causal association.
Association and Causation
- Association is the concurrence of two variables more often than would be expected by chance.
- Types of associations include spurious, indirect, direct (causal), one-to-one causal, and multi-factorial causal.
- Observing an association does not necessarily imply causation; a comparison is required to establish a causal relationship.
Examples of Association and Causation
- High serum homocysteine levels may be associated with an increased risk of IHD, but further comparison is needed to establish a causal relationship.
- The presence of Helicobacter pylori may be associated with duodenal ulcers, but further comparison is needed to establish a causal relationship.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
Test your knowledge on the concepts of association and causation in epidemiological studies, as discussed by Dr. Sireen Alkhaldi in the field of community medicine for the academic years 2023/2024 at the School of Medicine, The University of Jordan.
