Session 3 Flashcards
Cause (Mackie)
X is a cause of Y if X and Y occurred and, within a causal field, in the circumstances, Y would not have occurred if X had not occurred.
Cause (Rothman)
A cause of a disease event is an event, condition, or characteristic that preceded the disease event and without which the disease event would not have occurred at all or would have not occurred until some later time.
Causal Contrast
A comparison between the disease experience of an exposed individual and the disease experience the exposed individual would have had had they not been exposed (during the same time period).
Can be expressed in terms of ratio or a difference and in terms of risks, rates, or odds. However, risk ratio and risk difference are preferable when possible.
Causal explanation
Descriptions of how causes work.
Causal explanation comprises construct validity (the identification of the “active ingredients” of exposure and the mechanisms through which the exposure works) and exposure validity.
Causal Identification
The isolation of the causal effect of the exposure on the outcome as the sole plausible explanation for an association between the exposure and the outcome. This entails ruling out alternative explanations for an association (chance, confounding, selection, and measurement).
Causal Partner
When two or more exposures are in the same “causal pie”, we refer to them as causal partners. A casual partner is an exposure that works in concert with the exposure under investigation to cause disease.
Causal Field
Expresses the boundaries within which you ask a causal question. For example, when we talk about the causes of stroke, we often take for granted the fact that the human brain requires oxygen to function. We just consider that part of that taken-for-granted context in which all strokes happen, i.e. we do not consider the human brain requiring oxygen to be a cause because it is taken for granted. Causal fields are often left unarticulated, which can lead to miscommunication.
Component Cause
Each single cause within a causal pie
Counterfactual
What would have occurred under circumstances that differ from what did occur; usually used in epidemiology to refer to the disease experience of an exposed cohort under conditions of non-exposure.
Frenemy ?
Someone who is a really good friend, but who tells you the truth about problems in your work and argues with you about your positions.
Risk Factor
Used to mean a predictor of disease or simply an exposure.
Sufficient Component Cause Model
A heuristic device developed by Rothman to depict the concept of INUS causes.
INUS
An acronym developed by Mackie describing causes of interest as Insufficient but Necessary components of Unnecessary but Sufficient causes.
Fallible Falsification
It is grounded in the idea of theories competing for the best fit with the data. The theory that survives this test is considered “not yet falsified.” However, the falsification of a theory is based on numerous assumptions about the quality and meaning of the data and the fidelity of the expression of the theory. Therefore, it is recognized that this process is fallible. Nonetheless, such tests influence our beliefs in the theory: failing to pass such tests decreases our confidence in the theory.
