Bias + Error

Bias

Deviation of results/inferences from the truth, or processes that lead to systematic error.

Attrition Bias

Type of selection bias due to systematic differences between study groups in the number and the way participants are lost from a study.

Base Rate Fallacy

The tendency to ignore the base rate (general prevalence) in favor of individuating information.

Berkson‘s Bias

Selection bias that makes hospital cases & controls systematically different due to increased likelihood of being admitted based on exposure to risk & disease.

Confounding

An extraneous factor related to both exposure & outcome, causing distortion in the association.

Ecological Fallacy

Logical error that attributes characteristics of a group to individual members.

Hawthorne Effect

Modification of behavior by study participants due to awareness of being studied.

Healthy Worker Effect

Bias where employed individuals tend to be healthier, affecting mortality comparisons with the general population.

Information Bias

Distortion in the measure of association due to lack of accurate measurements of key study variables.

Interviewer/Recorder Bias

Systematic difference in soliciting, recording, or interpreting information across study groups.

Measurement Bias/Systematic Error

Errors in measuring data that result in deviation from the truth.

Lead Time Bias

Perception of longer survival due to earlier diagnosis of a condition.

Length Time Bias

Overestimation of survival duration due to excess detection of slow-progressing cases.

Loss to Follow Up Bias

Uneven loss of subjects over time between different study groups.

Panel Effect/Error

Participant fatigue due to being subjected to many interviews.

Publicity Bias

Bias in media selection and coverage of events or stories.

Recall Bias

Systematic differences in how subjects remember or report exposures/outcomes.

Selection Bias

Bias caused when subjects are selected based on a third variable, misrepresenting the target population.

Simpson’s Paradox

Statistical phenomenon where opposite conclusions can be drawn from the same data based on group divisions.

Social-Desirability Bias

Response bias where survey respondents answer according to societal expectations rather than personal beliefs.

Volunteer Bias

Differences between those who volunteer for studies and those who do not.

Non-differential Misclassification

Mixing between controls and cases when case definition isn't well defined.

Error

Difference between the true value and the measured value.

Random Error

Divergence from the truth due to random chance, yielding a zero net effect over many observations.

Type I Error

Rejection of a true null hypothesis (false positive).

Type II Error

Failure to reject a false null hypothesis (false negative).

Type III Error

Correctly rejects the null hypothesis for the wrong reason.

Type IV Error

Correctly rejects the null hypothesis but misinterprets the results.

Selection Bias (during recruitment)

Distortion of external validity due to non-representative sampling of the target population.

Ascertainment Bias

Systematic differences in data collection methods and assessment across study groups.

Information Bias (errors in data)

Errors from inaccurate measurement, misreporting, or inaccuracies in data collection.