Causality Flashcards

(45 cards)

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
Host
organism and usually a human
26
Epidemiology Triangle components
Host, Infectious Agent, Environment, Time
27
Environment
physical, biological, chemical, social, cultural
28
Each component of the Epidemiology Triangle has
time-related issues
29
Rothman's Causal Pies (1976)
Explain the multifactorial nature of causation for many noninfectious disease
30
Types of causal associations
Direct causal, indirect causal
31
Factors of causation
Predisposing, Enabling, Precipitating, Reinforcing
32
Predisposing
factors or conditions already present that cause susceptibility to a health-related state or event without actually causing it
33
Enabling
precedes a health-related state or event that allow it to be realized
34
Precipitating
factors essential to the development of a health-related state or event
35
Reinforcing
factors that aggravate and perpetuate a health-related state or event
36
Statistical association does not mean what?
a causal association
37
Causal guidelines
strength of association, consistency of association, temporality, biological plausibility, experimental evidence
38
Web of causation
graphics, pictorial, or paradigm representations of complex sets of events or conditions
39
P value < 0.01
99% association
40
Statistic steps
hypothesis, significance, sample, p-value, decide
41
Type 1 Error
- to reject a true null hypothesis - false positive - alpha
42
Type 2 Error
to accept a false null hypothesis false negative beta
43
Researcher's goal
to reject a null hypothesis
44
A type 1 error occurs when
the reseracher incorrectly rejects a true null hypothesis (false positive)
45
A type 2 error occurs when
the researcher fails to reject a null hypothesis