Sources of error in epidemiological research and methods to control them.
Epidemiology: The study of the distribution and determinants of health and disease in populations.
Bias: Any systematic error in the design, conduct, or analysis of a study that results in a deviation from the truth.
Confounding: A type of bias that occurs when the association between an exposure and an outcome is distorted by the presence of an extraneous variable that is associated with both the exposure and the outcome.
Types of bias: A description of the different types of biases that can occur in epidemiological studies, including selection bias, measurement bias, recall bias, and publication bias.
Selection bias: Bias that occurs when the selection of study participants is not random, such that the characteristics of the study sample differ from those of the target population.
Measurement bias: Bias that occurs when the measurement of the exposure, the outcome, or the covariates is not accurate, reliable, or valid.
Recall bias: Bias that occurs when participants in a study have memory of past events that is different from what actually happened.
Publication bias: Bias that occurs when the results of a study are not published, or are selectively published, based on the direction or strength of the association between the exposure and the outcome.
Control of bias: The methods used to minimize or eliminate bias in epidemiological studies, including randomization, blinding, standardization, matching, and adjustment.
Examples of bias and confounding: Examples of real-world situations where bias and confounding have affected the validity of epidemiological studies, including the associations between hormone replacement therapy and breast cancer, and between smoking and lung cancer.
Selection bias: Occurs when the sample chosen for a study is not representative of the population being studied, leading to misleading or incorrect conclusions.
Information bias: Occurs when the information collected or recorded during a study is inaccurate, leading to incorrect results.
Recall bias: Occurs when study participants have difficulty remembering past events accurately, leading to inaccurate data.
Reporting bias: Occurs when study participants provide inaccurate or incomplete information, leading to incorrect results.
Observer bias: Occurs when researchers unconsciously influence study results due to their own biases or expectations.
Sampling bias: Occurs when a sample selected for a study is not representative of the population being studied, leading to misleading results.
Lead-time bias: Occurs when a screening test or intervention detects a disease earlier than it would have been detected otherwise, leading to overestimated survival or treatment benefits.
Survivorship bias: Occurs when a study only includes individuals who have survived or otherwise met certain criteria, leading to biased and incomplete conclusions.
Confounding: Occurs when an extraneous factor is associated with both the exposure and the outcome, leading to incorrect conclusions about the relationship between the two.
Reverse causation: Occurs when the outcome of a study is used to explain the exposure, rather than the other way around, leading to incorrect conclusions.