Epi Study Guide - Leon Gordis
1.2X2 Table
a. cell b and c argue against the hypothesis.
b. cell b gives a false positive cell c gives a false negative
c. a cross classification of data where categories of one variable are presented in rows
and categories of another variable are presented in columns.
2.5 explanations for an association
a.Cause- a factor that produces a change in another factor
b.Confounding- situation in which a non-causal association between a given exposure and outcome is observed as a result of a third unobserved factor (called the confounder); the confounder is associated with the observed exposure and is the cause of the outcome
c.Reverse Time Order- outcome actually come before the exposure (opposite of hypothesis); the outcome is really the exposure and the exposure is really the outcome
d.Chance- to occur accidentally, without design, a coincidence
e.Bias- systematic error in design, conduct, or analysis of a study that results in a mistaken estimate
3.4 enduring epidemiological understandings
a. Health and disease are not distributed haphazardly in a population. There are patterns
to their occurrence. These patterns can be identified through surveillance of populations.
Examining these patterns of health and disease can help us formulate a hypothesis about their possible causes.
b. A hypothesis can be tested by comparing the frequency of disease in selected groups of people with and without the exposure to determine if the exposure and the disease are associated. When the exposure is hypothesized to have a beneficial effect, studies can be designed in which a group of people is intentionally exposed to the hypothesized cause and compared to a group that is not exposed. when an exposure is hypothesized to have detrimental effect, it is unethical to intentionally expose a group of people. In these circumstances, studies can be designed that observe groups of free living people
a. cell b and c argue against the hypothesis.
b. cell b gives a false positive cell c gives a false negative
c. a cross classification of data where categories of one variable are presented in rows
and categories of another variable are presented in columns.
2.5 explanations for an association
a.Cause- a factor that produces a change in another factor
b.Confounding- situation in which a non-causal association between a given exposure and outcome is observed as a result of a third unobserved factor (called the confounder); the confounder is associated with the observed exposure and is the cause of the outcome
c.Reverse Time Order- outcome actually come before the exposure (opposite of hypothesis); the outcome is really the exposure and the exposure is really the outcome
d.Chance- to occur accidentally, without design, a coincidence
e.Bias- systematic error in design, conduct, or analysis of a study that results in a mistaken estimate
3.4 enduring epidemiological understandings
a. Health and disease are not distributed haphazardly in a population. There are patterns
to their occurrence. These patterns can be identified through surveillance of populations.
Examining these patterns of health and disease can help us formulate a hypothesis about their possible causes.
b. A hypothesis can be tested by comparing the frequency of disease in selected groups of people with and without the exposure to determine if the exposure and the disease are associated. When the exposure is hypothesized to have a beneficial effect, studies can be designed in which a group of people is intentionally exposed to the hypothesized cause and compared to a group that is not exposed. when an exposure is hypothesized to have detrimental effect, it is unethical to intentionally expose a group of people. In these circumstances, studies can be designed that observe groups of free living people