Ch. 9 - Causality
risk factors
A characteristic, condition, or behavior, such as obesity, that increases the possibility of disease or injury; something that contributes to the production of an adverse health outcome.
Causal Interference
A conclusion about the presence of a health-related state or event and the reasons for its existence.
Analogy
A criterion in causal inference stating that analogous situations with previously demonstrated causal associations provide support of there being a causal association.
Biologic Gradient
A criterion in causal inference wherein an increasing risk of disease occurs with greater exposure.
Consistency of Association
A criterion in causal inference wherein the relationship between an exposure and outcome variable is replicated by different investigators in different settings with different methods.
Coherence
A criterion in causal inference wherein there is consistency with known epidemiologic patterns of disease.
Decision Tree
A decision tool that uses a graph or model of decisions and their possible consequences.
Construct Validity
A measurement that conforms to a theoretical construct; a test or scale that measures what it claims to measure.
Confidence Interval
A range of reasonable values in which a population parameter lies, based on a random sample from the population.
Method of Agreement
A single factor is common to a number of circumstances where the disease occurs at a high frequency.
null hypothesis
A statement that there is no association between the predictor and outcome variables in the population.
Hypothesis
A suggested explanation for an observed phenomenon or a reasoned proposal predicting a possible causal association among multiple phenomena.
At-risk behavior
An activity performed by a person that puts them at greater risk of developing a health-related state or event.
statistical inference
An inference or conclusion made about a population based on sampled data.
Koch's Postulates
Four criteria formulated by Robert Koch and Friedrich Loeffler in 1884 and refined and published by Koch in 1890 to establish a causal relationship between a causative microbe and a disease.
Web of Causation
Graphic, pictorial, or paradigm representations of complex sets of events or conditions caused by an array of activities connected to a common core or common experience or event.
Direct Causal Association
Has no intermediate factor and is more easily understood.
reinforcing factors
Have the ability to support the production and transmission of disease or conditions, or they have the ability to support and improve a population's health status and help control diseases and conditions.
Content Validity
Involves how well the assessment represents all aspects of the phenomena being studies.
Indirect Causal Association
Involves one or more intervening factors and is often much more complicated and difficult to understand than a direct causal association.
method of difference
Involves recognizing that if the frequency of a disease differs between two locations, it may be because a particular factor varies between those two places. For example, vastly different levels of colon cancer between Japan and the United States suggest that differences in diet may be the explanation.
Inductive Reasoning
Moving from specific observations to broader generalizations and theories.
Fish Bone Diagram
Provides a visual display of all possible causes that could potentially contribute to the disease, disorder, or condition under study.
precipitating factors
The factors essential for the development of diseases, conditions, injuries, disability, and death.
Method of concomitant variation
The frequency or strength of a risk factor varies in proportion to the frequency of the disease or condition.
power
The power of a statistical test measures the test's ability to reject the null hypothesis when it is actually false; power is directly associated with sample size. It is equal to 1 - beta.
predisposing factors
Those existing factors or conditions that produce a susceptibility or disposition in a host to a disease or condition without actually causing it. Predisposing factors precede the direct cause.
nominal data
Unordered categories or classes (e.g., gender, race/ethnicity, marital status, occupation).
type II error
When H0 is not rejected, but H0 is false.
Type I error
When the null hypothesis (H0) is rejected but H0 is true.
