Causal Inference Flashcards

1
Q

Definition of Cause, Causality, & Causal Inference

A
  1. Cause is a factor that gives rise to an effect (event).
  2. Causality is the potential that a specified change in a factor (cause) produces a predictable change in an event (effect)
  3. Causal inference is a reasoning process or the thought process, methods, and evidence used to support or refute a relationship as one of cause and effect
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2
Q

Definition of inference

A

Generalizing to a larger target group based on observations made in a subset of that group

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3
Q

T/F: Causal inference is a deductive reasoning process

A

False. It is an inductive reasoning process (from small to large)

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4
Q

T/F: Randomized Trail is the best choice for “causality” since we have control over cause/exposure.

A

True

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5
Q

Assigning Evidence Levels for Causation (3 levels)

A
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6
Q

General categories of observed associations (3)

A
  1. Chance (interval estimation, hypothesis testing)
  2. Spurious (artifactual due to bias)
  3. True (causal or noncausal [confounding] ?)

If after dealing with confounding, the association is gone, then there’s no causality here. The observed association is solely due to the confounding.

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7
Q

T/F: Single factor model is reasonable to be used when studying chronic disease

A

False. It is reasonable to be used when studying infectious disease. Multifactorial model is used when studying chronic disease.

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8
Q

2 types of causal relationships in modern concepts

A
  1. Component (necessary): a factor that is required, but not singly responsible, for disease occurrence (also called component cause)
  2. Sufficient (required): a set of minimal conditions (component causes) that operate collectively to produce disease (they are actually causal pathway)

When all the component causes occur, sufficient cause is formed.

Intervening on a component cause may effectively lower disease by rendering the other components insufficient.

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9
Q

Conceptual scheme of 3 sufficient causal paths for a hypothetical disease

A
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10
Q

Guidelines for evaluating the evidence for causality

A

consistency (in other studies)

temporality (exposure precedes disease)

biologic gradient (dose-response)

Coherence

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