Lecture 5 Sp24 Flashcards
(37 cards)
What is the impact of misclassification on the odds ratio (OR)?
The OR can be biased towards or away from the null depending on the type of misclassification.
Differential misclassification can inflate or deflate the OR.
How is the prevalence of exposure calculated among cases?
Prevalence of exposure among cases = (Number of exposed cases / Total cases)
Example: (48/76) = 63.2%
What is the formula for calculating the odds ratio (OR)?
OR = (a/c) / (b/d)
Where a, b, c, and d are the cells in a 2x2 contingency table.
What is selection bias?
Selection bias occurs when the inclusion of participants in a study is influenced by their exposure status or disease status.
It can lead to systematic differences between those included and those not included.
What are some common types of selection biases?
- Volunteer Bias
- Refusal Bias
- Berkson’s Bias
- Neyman Bias
- Survival Bias
- Publicity Bias
- Sampling Bias
- Non-response Bias
- Membership Bias
What strategies can reduce selection bias?
- Reducing use of volunteers
- Increasing participation
- Choosing similarly selected comparison groups
- Careful eligibility criteria
- Awareness in recruitment strategies
- Blinding
True or False: Ascertainment bias relates to the differential diagnosis of a condition among exposed versus non-exposed individuals.
True
This bias can occur due to differential medical surveillance or referral patterns.
What is information bias?
Information bias is the inaccurate classification of study subjects with respect to disease or exposure status.
It can result in exposure misclassification or disease misclassification.
Fill in the blank: The __________ effect refers to the phenomenon where healthy individuals are more likely to be included in studies.
[Healthy Worker Effect]
What type of bias can occur when patients recall their exposure status differently based on their disease status?
Recall Bias
This is a common type of information bias.
What is the difference between selection bias and information bias?
Selection bias relates to who is included in the study, while information bias pertains to the accuracy of data collected on exposure and disease status.
Selection bias affects external validity; information bias affects internal validity.
What is an example of detection bias?
Detection bias occurs when an exposure causes a sign or symptom that leads to increased detection of a condition.
Example: Exogenous hormones causing increased vaginal bleeding, leading to more endometrial cancer diagnoses.
What is the definition of prevalence?
Prevalence is the proportion of a population found to have a condition at a specific time.
It is calculated as the number of existing cases divided by the total population.
True or False: Non-response bias occurs when certain individuals do not participate in a study, potentially skewing results.
True
This bias can affect the representativeness of the study sample.
What is the consequence of using prevalent cases instead of incident cases in a study?
Using prevalent cases can lead to survivor treatment selection bias and may not accurately reflect the disease’s natural history.
It can result in inclusion of individuals with longer disease duration.
How can you assess the impact of misclassification on study results?
By comparing the resulting tables from misclassification errors to determine changes in OR and prevalence.
This can reveal whether the bias is towards or away from the null.
Fill in the blank: __________ bias occurs when the knowledge of exposure status influences the diagnostic process.
[Exposure suspicion bias]
What is the true odds ratio (OR) in the given example?
True OR = 2.25
This OR reflects the actual relationship between exposure and disease.
What are the main analytic methods used in epidemiologic studies?
Calculation of measures of disease frequency, association, impact, and corresponding 95% CIs
These methods are essential for evaluating public health data.
What types of bias should students be able to identify in a study?
Selection and information bias, including misclassification
Recognizing these biases is crucial for valid study conclusions.
What is confounding in epidemiology?
A distortion in a measure of effect due to a third variable that is associated with both the exposure and the outcome
Confounding can lead to misleading conclusions if not controlled.
What is the general rule for identifying a confounding variable?
The confounding variable must be causally associated with the outcome and associated with the exposure, but not an intermediate variable
This helps in distinguishing confounders from other variables.
How does confounding differ from bias?
Confounding is a real association due to a third variable, while bias is a systematic error in data collection
Understanding this distinction is important for accurate data interpretation.
What is the impact of misclassification on study results?
Can lead to incorrect estimation of disease association and bias results
Misclassification can occur when exposure histories are not accurately collected.
