Epidemiology Exam 3 Flashcards
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Questions and Answers

What are the levels of the dependent variable for the study involving the anti-nausea drug?

  • Mothers who gave birth to infants with a birth defect vs. mothers who gave birth to infants without a birth defect
  • Babies who took the anti-nausea drug vs. babies who did not take the anti-nausea drug
  • Both A and B (correct)
  • Neither A nor B

    • What measure of comparison is most appropriate for the study design concerning mothers' recall of anti-nausea medication use?

  • The exposure odds ratio (OR) (correct)
  • The relative risk (RR)
  • The rate ratio (RR)
  • The population attributable risk percent (PAR%)

    • What is the formula for the odds ratio?

    OR = a × d / (b × c)

    Which statements regarding bias and odds ratio are true? (Select two)

    <p>The bias is toward the null value</p> Signup and view all the answers

    Which type of bias are the investigators likely investigating?

    <p>Recall bias</p> Signup and view all the answers

    Selection bias is most likely to occur in which types of studies?

    <p>Both Retrospective Cohort and Case-Control Studies</p> Signup and view all the answers

    Identify three ways confounding can be controlled in the design phase of an epidemiologic study.

    <p>Randomization, restriction, matching</p> Signup and view all the answers

    Identify three ways confounding can be controlled in the analysis phase of an epidemiologic study.

    <p>Standardization, stratified analysis, multivariate analysis</p> Signup and view all the answers

    Is it better to control for confounding at the design phase or the analytic phase of a study?

    <p>Design phase</p> Signup and view all the answers

    What are the limitations of controlling for confounding in the design phase of an epidemiologic study?

    <p>Matching is only possible for known measured confounders; restriction can limit sample size; randomization is limited to experimental studies.</p> Signup and view all the answers

    What are the limitations of controlling for confounding in the analysis phase of an epidemiologic study?

    <p>Stratified analysis is difficult for many confounders; multivariate analysis has assumptions; standardization has limitations.</p> Signup and view all the answers

    What is residual confounding?

    <p>Confounding that remains even after some confounding variables have been controlled.</p> Signup and view all the answers

    Do you suspect socioeconomic status (SES) is a confounder based on examining the crude and the stratified data?

    <p>Yes</p> Signup and view all the answers

    Is SES a confounder in this analysis?

    <p>Yes</p> Signup and view all the answers

    What is the magnitude of the confounding?

    <p>128%</p> Signup and view all the answers

    Identify the independent variable, dependent variable, and potential confounding factor in the study about exercise habits and heart attacks.

    <p>Independent variable: exercise habits; Dependent variable: heart attack; Potential confounding factor: sex at birth</p> Signup and view all the answers

    What is happening with the observed measure of association when positive confounding is present?

    <p>The observed association is exaggerating the true association.</p> Signup and view all the answers

    What is happening with the observed measure of association when negative confounding is present?

    <p>The observed measure of association is hiding the true measure.</p> Signup and view all the answers

    Which statement about smoking in relation to heart disease is false?

    <p>Smoking is a mediator because it lies in the causal pathway between coffee drinking and heart disease.</p> Signup and view all the answers

    What is the difference between a mediator and a confounder?

    <p>A mediator is in the causal pathway, confounders are not.</p> Signup and view all the answers

    Mediators cannot be in the causal pathway between exposure and disease.

    <p>False</p> Signup and view all the answers

    Confounding is the same as random error.

    <p>False</p> Signup and view all the answers

    It may be possible to control for confounding in both the design phase and the analytic phase of research studies.

    <p>True</p> Signup and view all the answers

    Define random error.

    <p>An unsystematic error that arises from chance.</p> Signup and view all the answers

    In which types of studies can random error occur?

    <p>Random error occurs to some extent in all studies.</p> Signup and view all the answers

    What effect(s) does having random error have in epidemiologic studies?

    <p>Creates the appearance of an association when there is none; or masks an association that really exists.</p> Signup and view all the answers

    What are the top two causes of random error in epidemiologic studies?

    <p>Measurement error and sampling variability.</p> Signup and view all the answers

    Interpret the RR measure from the researcher studying sedentary computer programmers' risk of cardiovascular disease.

    <p>Sedentary computer programmers have 4.3 times the risk of cardiovascular disease compared to non-computer programmers.</p> Signup and view all the answers

    What does the term 'validity' mean?

    <p>Lack of random error, bias, and confounding (accurate to the true value)</p> Signup and view all the answers

    What are the three alternative explanations to consider when assessing the validity of a study? Define each.

    <p>Bias: A systematic error in the design or conduct of study that leads to an erroneous association between the exposure and disease. Confounding: The mixing of effects between the exposure, disease, and a third variable. Random error: The probability that the observed result is attributable to chance.</p> Signup and view all the answers

    Define generalizability.

    <p>A judgment in which the investigator relates the conclusions of a study beyond the study setting and population to a broader setting and population.</p> Signup and view all the answers

    Is it possible to have both random error and systematic error in the same study?

    <p>True</p> Signup and view all the answers

    Explain what happens when there is bias in a study that biases results towards the null.

    <p>Magnitude of Association will be smaller than the true value, direction will be closer to the null value, and true association is underestimated.</p> Signup and view all the answers

    Explain what happens when there is bias in a study that biases results away from the null.

    <p>Magnitude of Association will be larger than the true value, direction will be farther away from the null value, and true association is overestimated.</p> Signup and view all the answers

    If bias occurs in a study, it is possible for us to fix or remove it when we do the analysis.

    <p>False</p> Signup and view all the answers

    Briefly describe when/how selection bias occurs in an epidemiologic study.

    <p>An error that arises mainly from systematic differences in selecting the study groups.</p> Signup and view all the answers

    What types of studies is selection bias more likely to occur?

    <p>Case-control and retrospective cohort studies.</p> Signup and view all the answers

    List specific types of selection bias.

    <p>Control selection bias, healthy worker effect, self-selection bias, differential losses to follow-up, differential surveillance.</p> Signup and view all the answers

    What can be done to fix selection bias?

    <p>Little can be done to fix this bias once it has occurred.</p> Signup and view all the answers

    How does selection bias impact measures of association?

    <p>It can bias an association either toward or away from the null.</p> Signup and view all the answers

    Name methods to avoid selection bias.

    <p>Using the same criteria for selecting cases and controls, obtaining high participation rates, and accounting for differential losses to follow-up.</p> Signup and view all the answers

    Define information bias.

    <p>An error that arises from systematic differences in the way that information on exposure and disease is obtained from study groups.</p> Signup and view all the answers

    What are three types of information bias?

    <p>Recall bias, interviewer bias, and measurement error.</p> Signup and view all the answers

    What is recall bias?

    <p>A type of information bias whereby a differential level of accuracy in the information provided by compared groups occurs.</p> Signup and view all the answers

    What is interviewer bias?

    <p>A type of information bias in which there is a systematic difference in soliciting, recording, or interpreting interview information.</p> Signup and view all the answers

    What is measurement/misclassification error?

    <p>Nonsystematic error in assessing the exposure and outcome.</p> Signup and view all the answers

    List some ways to prevent/avoid interviewer bias.

    <p>Masking interviewers and subjects to the study hypothesis, using control groups, and careful questionnaire design.</p> Signup and view all the answers

    What is differential misclassification?

    <p>Errors on one axis (exposure or disease) that are related to the other axis.</p> Signup and view all the answers

    What is non-differential misclassification?

    <p>Errors on one axis that are unrelated to the other axis.</p> Signup and view all the answers

    What can non-differential misclassification do to the true value for a measure of association?

    <p>It always results in a bias toward the null value.</p> Signup and view all the answers

    What can differential misclassification do to a measure of association?

    <p>The measure could be biased away from the null or biased toward the null.</p> Signup and view all the answers

    When does information bias occur?

    <p>It occurs after subjects have entered the study.</p> Signup and view all the answers

    List the three alternative explanations to consider for internal validity.

    <p>Bias, confounding, chance (random error).</p> Signup and view all the answers

    Methods to avoid information bias?

    <p>Masking interviewers, using control groups, careful designing of questionnaires.</p> Signup and view all the answers

    What does selection bias have to do with?

    <p>Who takes part in your study.</p> Signup and view all the answers

    When does selection bias occur?

    <p>When people participating in a study are different from the base population that you want to study.</p> Signup and view all the answers

    What can selection bias lead to?

    <p>An observed association that differs from what would have been obtained from the target population.</p> Signup and view all the answers

    Bias can occur if controls are more (or less) likely to be selected based on their exposure status.

    <p>True</p> Signup and view all the answers

    Differential participation is a type of selection bias.

    <p>True</p> Signup and view all the answers

    Bias occurs when an investigator chooses to analyze only a subset of participants in a study.

    <p>False</p> Signup and view all the answers

    Only once a study is deemed as having internal validity is it appropriate to consider generalizability.

    <p>True</p> Signup and view all the answers

    Having participants refuse to participate in a study can lead to self-selection bias.

    <p>True</p> Signup and view all the answers

    Bias can be introduced at any stage of a study.

    <p>True</p> Signup and view all the answers

    Loss to follow up results in selection bias in a cohort study when the loss is associated with both the exposure and outcome.

    <p>True</p> Signup and view all the answers

    If bias occurs in a study, it is possible to fix/correct with special analytic methods.

    <p>False</p> Signup and view all the answers

    Define confounding.

    <p>The mixing of effects between an exposure, an outcome, and a third extraneous variable known as a confounder.</p> Signup and view all the answers

    What are the three criteria for a variable to be considered a confounder?

    <p>(1) It is associated with the exposure in the population that produced the cases, (2) it is an independent cause or predictor of disease, (3) it is not an intermediate step in the causal pathway between the exposure and disease.</p> Signup and view all the answers

    What might be considered a confounder in epidemiological research?

    <p>Age, sex, race/ethnicity.</p> Signup and view all the answers

    What is positive confounding doing regarding the true value for a measure of association?

    <p>Confounding that pulls the crude measure of association away from the null.</p> Signup and view all the answers

    What is negative confounding doing regarding the true value for a measure of association?

    <p>Confounding that pulls the crude measure of association toward the null.</p> Signup and view all the answers

    What could be the relationship between modest alcohol consumption and coronary heart disease according to a directed acyclic graph?

    <p>MAC --&gt; HDL --&gt; CHD.</p> Signup and view all the answers

    According to the directed acyclic graph, what is the exposure of interest, health outcome, and potential confounder?

    <p>Exposure: MAC, Health outcome: CHD, Potential confounding variable: HDLs.</p> Signup and view all the answers

    What is a mediator variable?

    <p>A variable that is a step in the causal pathway between an exposure and a disease.</p> Signup and view all the answers

    Confounding is one source of systematic error in epidemiological research.

    <p>True</p> Signup and view all the answers

    Confounding can be thought of as a failure of the comparison group to reflect the counterfactual experience of the control group.

    <p>True</p> Signup and view all the answers

    Confounding always biases the resulting measures of association away from the null.

    <p>False</p> Signup and view all the answers

    Mediator variables are confounding variables.

    <p>False</p> Signup and view all the answers

    Confounding variables are considered independent variables.

    <p>True</p> Signup and view all the answers

    Confounding variables result from random error.

    <p>False</p> Signup and view all the answers

    Is it possible to control for confounding in the design phase of research studies?

    <p>True</p> Signup and view all the answers

    Is it possible to control for confounding in the analysis phase of research studies?

    <p>True</p> Signup and view all the answers

    The crude measure of association is the measure obtained from study data.

    <p>True</p> Signup and view all the answers

    The true RR=2.5, but the confounded RR=3.8. This is an example of negative confounding.

    <p>False</p> Signup and view all the answers

    In a case-control study, what are the levels of the independent variable?

    <p>Mothers who took the anti-nausea drug vs. mothers who did not take the anti-nausea drug.</p> Signup and view all the answers

    Study Notes

    Validity and Bias

    • Validity denotes the accuracy of a study, characterized by the absence of random error, bias, and confounding.
    • Three critical alternative explanations to assess study validity:
      • Bias: Systematic error that skews the perceived relationship between exposure and disease.
      • Confounding: Influence of a third variable that distorts the true association between exposure and disease.
      • Random Error: Variability in study results that occurs by chance, lacking a specific cause.

    Generalizability and Association

    • Generalizability refers to extending study conclusions beyond the specific study population and setting.
    • Bias can lead to both random and systematic errors simultaneously.
    • When bias drives results toward the null hypothesis, the true association is underestimated; when it moves away, the true association is overestimated relative to the null.

    Selection Bias

    • Selection bias arises from differences in how study groups are chosen.
    • More common in case-control and retrospective cohort studies; also a concern in prospective cohort studies due to differential follow-up.
    • Strategies to mitigate selection bias: consistent case/control selection criteria, high participation rates, and effective tracking methods.
    • The impact of selection bias can distort association metrics, shifting them either towards or away from the null.

    Information Bias

    • Information bias occurs from systematic discrepancies in how data on exposure and disease is gathered from participants.
    • Types of information bias include:
      • Recall Bias: Differences in accuracy of reported information between groups.
      • Interviewer Bias: Systematic differences in data collection by interviewers.
      • Measurement Error: Nonsystematic errors that affect both exposure and outcome assessment.
    • Preventive methods for information bias involve careful study design and data collection methods.

    Confounding Variables

    • Confounding is the interplay of an exposure, outcome, and a third variable that alters the perceived relationship.
    • A valid confounder meets three criteria:
      • Associated with the exposure in the population being studied.
      • Acts independently as a predictor of the disease.
      • Is not part of the causal pathway between exposure and disease.

    Misclassification

    • Differential Misclassification: Errors are related to a specific axis (exposure or disease) and can bias outcomes in either direction.
    • Non-Differential Misclassification: Errors on one axis unrelated to the other, generally biasing results towards the null hypothesis.
    • Preventing misclassification focuses on enhancing data collection accuracy through various measurement techniques.

    Case-Control Study Framework

    • In case-control studies, determining how participants recall past exposure can affect odds ratio calculations.
    • Bias introduced through inaccurate reporting can shift odds ratios toward the null value due to non-differential misclassification.
    • Understanding how exposure and outcome relate in these studies is critical for evaluating true associations.

    Statistical Concepts and Directions

    • Adjusting for confounding can be achieved during both study design and analysis phases.
    • The "crude measure of association" represents initial estimates without adjustment for confounding factors.
    • Direction of bias can vary significantly depending on whether confounding leads to overestimation or underestimation of the true association.

    Key Takeaways

    • Recognizing and addressing different biases is essential to maintain the integrity of epidemiological research.
    • Effective study design, critical evaluation of variables, and comprehensive data collection methodologies are key to minimizing errors.
    • Continuous vigilance for biases at all study stages can enhance the reliability and applicability of research findings.### Bias in Epidemiological Studies
    • The magnitude of the Odds Ratio (OR) is often less than the true value due to bias.
    • Investigators commonly investigate types of bias such as recall bias and interviewer bias, both of which are forms of information bias.
    • Selection bias is prevalent in case-control studies and retrospective cohort studies, leading to incorrect associations.

    Confounding Control

    • Confounding can be managed during the design phase using:
      • Randomization
      • Restriction
      • Matching
    • In the analysis phase, confounding can be controlled through:
      • Standardization
      • Stratified analysis
      • Multivariate analysis
    • Controlling confounding during the design phase is generally more effective than during the analysis phase.

    Limitations in Confounding Control

    • Matching is challenging due to its dependence on known confounders; may incur high costs and time.
    • Restriction limits generalizability and sample size and may not fully control for confounders.
    • Randomization is primarily applicable to experimental studies and is less effective with smaller samples.
    • In the analysis phase, stratified analysis is complex with multiple confounders, and multivariate analysis requires stringent model assumptions.

    Residual Confounding

    • Residual confounding refers to unaddressed confounding variables that remain even after some confounding has been controlled.

    Confounding Example

    • If socioeconomic status (SES) shows different Relative Risks (RR) across stratifications, and an SES-adjusted RR differs significantly, SES is identified as a confounder.

    Observed vs True Association

    • Positive confounding results in the observed association exaggerating the true association, moving farther from the null value.
    • Negative confounding causes the observed association to mask the true association, pulling it toward the null value.

    Mediators vs Confounders

    • A mediator is part of the causal pathway between an exposure and disease, while a confounder is not.
    • It is possible to control for confounding in both design and analytic phases of research.

    Random Error

    • Random error encompasses unsystematic errors due to chance and can occur in all study types.
    • It can create false associations or obscure true associations.
    • Causes include measurement error and sampling variability, both contributing to random error in epidemiological studies.

    Hypothesis Testing Outcomes

    • Null hypothesis (H0) may be true and either not rejected (correct conclusion) or mistakenly rejected (Type I error).
    • Alternative hypothesis (HA) may be true and either not confirmed (Type II error) or correctly supported (correct conclusion).

    Statistical Practice

    • The p-value indicates the probability of observing results due to chance if the null hypothesis is true.
    • A confidence interval quantifies random error, indicating variability around a measure and providing a range in which the true effect lies.
    • Wider confidence intervals signify greater random error and reduced precision, while narrower intervals indicate less random error and more precision.

    Risk Interpretation

    • A calculated Relative Risk (RR) of 4.3 indicates that sedentary computer programmers have 4.3 times higher risk of cardiovascular disease compared to non-computer programmers, based on a p-value of 0.02.

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    Test your knowledge on validity and alternative explanations in epidemiology with this set of flashcards. Perfect for review before Exam 3. Each card presents key concepts clearly and concisely.

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