instructor resource chapter 8 copyright © scott b. patten, 2015. permission granted for classroom...
TRANSCRIPT
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Instructor Resource
Chapter 8
Copyright © Scott B. Patten, 2015.
Permission granted for classroom use with Epidemiology for Canadian Students: Principles, Methods & Critical Appraisal (Edmonton: Brush Education Inc. www.brusheducation.ca).
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Chapter 8. Selection error and selection bias in descriptive
studies
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Objectives
• Define selection bias as a type of systematic error arising from participation or nonparticipation in a study.• Identify sources of selection bias: selection itself,
nonconsent, attrition, and missing data• Describe the mechanism by which defective selection
can introduce bias into an estimated frequency such as prevalence.• Describe the direction of bias in a defective
prevalence study in which selection depends on disease status.
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Sources of error Type of bias
Random error Chance N/A
Systematic error
• Measurement error
Flaws in study design (flawed measurement leading to misclassification)
Misclassification bias
• Selection error Flaws in study design (flawed sampling procedures that choose participants)
Selection bias
Other factors related to participation (e.g., subjects withdrawing from a study)
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Selection bias
Selection bias is a type of systematic error that results from study-design defects, and other factors, that affect who participates in an epidemiologic study.
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Selection bias due to sampling procedures
• To understand flawed sampling procedures, it helps to consider ideal sampling procedures.• Ideal sampling procedures deliver probability
samples, where the probability of selection for each member of the sample is known.• Probability samples can be simple (e.g., simple
random samples) or complex (e.g., where selection probabilities differ among respondents).
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Selecting a simple random sample
• The first step is to identify a sampling frame.• Then, randomly select observations from that
sample.
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Sampling frames
Examples of sampling frames include:• area-based frames (e.g., based on geography)• telephone-based frames (lists of telephone
numbers)• mailing-based frames (lists of mailing addresses)• disease registries
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A note about telephone frames• Telephone survey methods are of declining
importance in epidemiology due to difficulties in obtaining a representative sample in this way.• Since a listing of telephone numbers does not
include unlisted numbers, random-digit dialing or random-digit substitution is preferable.
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Sampling when a frame is not available
Possibilities include:• random digit dialing
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Selection error from other factorsAll of the following are sources of selection error:• nonconsent• attrition• missing data*
* Missing data are often handled using specialized techniques that allow educatedguesses to be made about the likely values of the missing variables (imputation), but ifmissing data results in nonparticipation (e.g., the respondents with missing data are Excluded form calculation of a parameter), the implications are the same.
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Ethical issues
• Informed consent is required for research to respect personal autonomy (respect for persons).• Other ethical principles include:• beneficence• nonmalfeasance• utilitarian principle• confidentiality• privacy• justice
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Mechanisms of selection biasWith selection bias, the prevalence estimate from a study is related both to the frequencies in the population and to selection.
e (prevalence )=A x pse 𝑙𝑒𝑐𝑡𝑖𝑜𝑛
( A x psel ection )+ (B x psel ection )
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Mechanisms of selection biasNote that if there is only 1 selection probability (e.g., a simple random sample), all of the pselection terms will disappear and the right-hand side of the equation will reduce to A/(A+B) or PREVALENCE
e ( prevalence)=A x pselection
¿ ¿
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Mechanisms of selection bias• But what if the pselection associated with those who have
the disease (A) is greater than that of those without (B)?• Will the expected value of the prevalence estimate still
resemble PREVALENCE? Will it be too high or too low?• Can you think of a reason why this might occur?
e ( prevalence)=A x pselection
¿ ¿
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Mechanisms of selection bias• What if the pselection associated with those who do
not have the disease (B) is greater than that of those with the disease (A)?• Can you think of a reason why this might occur?
e ( prevalence)=A x pselection
¿ ¿
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