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Epidemiology HS 301 > Causality > Flashcards

Causality Flashcards

1
Q

Pros of samples

A

can be studied more quickly than larger populations

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2
Q

Hypothesis testing

A

based upon what is commonly believed (the status quo)

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3
Q

Alternative hypothesis (H1)

A

statement that contradicts the null hypothesis

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4
Q

6 steps for evaluating hypotheses

A
  1. Formulate the Ho in statistical terms (Ho: Odds ratio = 1)
  2. Formulate the H1 in statistical terms (H1: Odds Ratio = 1).
  3. Select the level of significance for the statistical test and sample size (generally 0.05 or conservatively 0.01)
  4. Select the appropriate test stastic and identify the degrees of freedom and the critical value
  5. Collect the data and estimate the measur eof association and test statistic
  6. If the observed measure exceeds the critical value, reject Ho in favor of H1; otherwise do not reject Ho
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5
Q

The null hypothesis is assumed to be correct unless

A

there is sufficient evidence from the sample data to indicate otherwise

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6
Q

A tentative suggestion that a cerain phenomenon exists

A

research hypothesis

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7
Q

P value

A

the probability for evaluating the role of chance; ranges from 0 to 1

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8
Q

Small p value (> or = 0.05)

A

the result is unlikely to be a product of chance

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9
Q

Confidence intervals

A

range of reasonable values in which a population parameter lies that is based on a random sample from the population

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10
Q

When sample size increases

A

the role of chance decreases

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11
Q

To minimize chance

A

increase sample size

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12
Q

Bias

A

deviation from the truth

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13
Q

Random error

A

incorrect result due to chance

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14
Q

Systematic error

A

incorret result due to bias

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15
Q

Confounding

A

a third factor that influences the relationship between an expoure and disease outcome

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16
Q

Determinants

A

causes/factors

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17
Q

Epidemiology

A

the study of the distribution and determinants of health-related states or events in human populations and the application of this study to the prevention and control of health problems

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18
Q

Identifying what determines (cause) disease allows us to

A

prevent and control the health problem rather than react to it

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19
Q

Identifying what determines (cause) disease allows us to

A

prevent and contorl the health problem, rather than react to it

20
Q

Cause

A

a variable that precedes a health outcome and is necessary for its occurrence

21
Q

When is a causative factor “necessary”

A

if an environmental exposure is required for the outcome to occur

22
Q

Epidemiology Triangle components

A

Host, Infectious Agent, Environment, Time

23
Q

Epidemiology Triangle

A

a model that characterizes infectious disease causation showing the interaction between agent, host, environment, and time

24
Q

Agent

A

causative factors such as a pathogen or chemical

25
Q

Host

A

organism and usually a human

26
Q

Epidemiology Triangle components

A

Host, Infectious Agent, Environment, Time

27
Q

Environment

A

physical, biological, chemical, social, cultural

28
Q

Each component of the Epidemiology Triangle has

A

time-related issues

29
Q

Rothman’s Causal Pies (1976)

A

Explain the multifactorial nature of causation for many noninfectious disease

30
Q

Types of causal associations

A

Direct causal, indirect causal

31
Q

Factors of causation

A

Predisposing, Enabling, Precipitating, Reinforcing

32
Q

Predisposing

A

factors or conditions already present that cause susceptibility to a health-related state or event without actually causing it

33
Q

Enabling

A

precedes a health-related state or event that allow it to be realized

34
Q

Precipitating

A

factors essential to the development of a health-related state or event

35
Q

Reinforcing

A

factors that aggravate and perpetuate a health-related state or event

36
Q

Statistical association does not mean what?

A

a causal association

37
Q

Causal guidelines

A

strength of association, consistency of association, temporality, biological plausibility, experimental evidence

38
Q

Web of causation

A

graphics, pictorial, or paradigm representations of complex sets of events or conditions

39
Q

P value < 0.01

A

99% association

40
Q

Statistic steps

A

hypothesis, significance, sample, p-value, decide

41
Q

Type 1 Error

A
  • to reject a true null hypothesis
  • false positive
  • alpha
42
Q

Type 2 Error

A

to accept a false null hypothesis
false negative
beta

43
Q

Researcher’s goal

A

to reject a null hypothesis

44
Q

A type 1 error occurs when

A

the reseracher incorrectly rejects a true null hypothesis (false positive)

45
Q

A type 2 error occurs when

A

the researcher fails to reject a null hypothesis

Epidemiology HS 301 (9 decks)

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