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BMS I > EBM Day 2 > Flashcards

EBM Day 2 Flashcards

1
Q

Statistical Hypot

A

is there difference between groups,

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2
Q

Ho

A

no association between x and y

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3
Q

Fail to reject means

Reject null

A

fail to reject, never prove hypo because may be due to the 5% chance

consider possibility of type 1 error (unless p

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4
Q

statistically sig means

A

result where reject Ho at whatever alpha level we set

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5
Q

type 1 vs type 2 errors

A

t1-fail to reject null when true

t2- reject null when false

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6
Q

T1 and T2 in releation to power, alpha, and beta

and what is alpha, beta, power

A

alpha-willingness to be wrong (reject null when we shouldn’t)
beta-=t2 error=willingess to fail to reject a false Ho (typically .1 or .2)
Power-1-beta=power to correctly reject false null (80%)-ability to detect or verify difference is real

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7
Q

Sensitivity and Specificity

A

sensitivity=true positives/(true positives and false negs)

specificity=true negatives/(true negatives and false positives)

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8
Q

power determination

A

alpha (more stringent, less power), beta (too lax, less power), prevalence of condition, magnitude of effect, sample size (more subjects make more power)

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9
Q

Effect size

A

how big of a difference we look for

smaller effect size=larger the sample size needed

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10
Q

Bonferroni adjustments

A

adjusting for multiple comparisons-increases type 2 error and decreases power

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11
Q

T test

A

-compares difference between two means divided by variability in sample
assumes equal variances

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12
Q

Mann Whitney U

A

Non parametric-operates on ranks

ignores mean and median

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13
Q

Minimize T1 and T2 at same time?

A

there is always a tradeoff
Tolerate type 1 if false positive okay
Tolerate type 2 if if procedure may be serious danger to patient

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14
Q

Increase power

A

lower beta, raising alpha, raising sample size, testing a large difference

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15
Q

2x2 table

A

Draw=THERE ARE QUESTIONS AT END OF HIS SLIDES

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16
Q

Risk and how offset

A

Probabilty of an outcome

Offset by intervention, treatment, prevention

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17
Q

Primary, secondary, tertiary prevention

A

before disease
Catching early
treatment

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18
Q

Pathogenic Triangle

A

host, environment, agents

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19
Q

Risk factors

A

Anything which increase likelihood of disease

ex. other disease, environmental, genetic

20
Q

Environmental risk factors (5) and examples

A

chemical (oxidation substances), physical (radioactivity), biological (pathogens), psychosocial (stress), mechanical (heavy lifting)

21
Q

2x2 of Karaoke job Decision latitude

A

low demand, low decision-passive
low demand, high decision-low -strain (scientist)
high demand, low decision-high- strain
high demand, high decision-active (doctor)

22
Q

Latency

A

Period between exposure and disease

23
Q

Cohort study main question

A

Asking if incidence of an outcome in a group who were exposed different (greater/less) compared to incidence among similar group who were unexposed?

24
Q

Cohort study result

A

Get incidence rate of exposed

Get risk ratio, relative risk/difference when compare

25
Q

Picking a cohort

A

Should not have outcome when picked
All should be at risk for outcome
Should be observed over natural history of disease
Observe over entire time of disease

26
Q

How to do cohort study

A

Find population where everyone at risk for something

Divide people into two groups depending on exposure to risk factor

27
Q

Cohort study other names

A 
incidence study
longitundinal study
prospective study
retrospective
historical
28
Q

Retrospective vs Prospective Cohort

A

Prospective takes much longer time, assemble cohorts in present, choose which risk factors/confounder to measure, chose how to measure
Retrospective may not have all data you need, cohorts assembled in past (by medical records), outcome accessed at later date

29
Q

Relative Risk

A

a/(a+b)/c/(c+d) draw

30
Q

Type 1/2 and false … error

A
  1. false postive

2. false negative

31
Q

Causes of error

A

Chance-nondifferential-random error-type 2 error
Bias-can be differential or non differential-type 1 error
Confouding

32
Q

Differential vs Nondifferntial bias regarding direction

A

Differential-towards one direction or another

Nondifferential-towards norm

33
Q

Cross sectional study

A

Measure disease and time at same time

34
Q

Confounding Variable

A

Associated with DV and IV but not in pathway

Can cause t1 or t2 error

35
Q

Confounding by indication (and error associated with it)

A

Sicker patients are more likely to be treated and to have worse outcomes
Increase T1 error
ex. use of drug for really sick people associated with increased mortality because people are really sick (even if it helps)

36
Q

Decrease confoundng

A

Randomization-distribute potential confounders between groups

Restriction-restrict a confounding variable during study duration (lower sample size and power though)

Matching-match with people of similar characteristics

Stratifcation-data separated by potential confounder-if confoudner present-risk ratios lower than in unstratified data (risk due to confounding no difference between strata)

MV adjustment-control effects of many variables simulataneously

37
Q

Effect modification

A

effect mods-variables that change effect of exposure of interest on risk of disease

AKA- interaction

One exposure effects other exposure

38
Q

Selection Bias

A

Selective differences between comparison groups that impact relationship between exposure and outcome

39
Q

Selection bias examples (4)

A

healthy worker effect
Self selection bias
Withdrawal bias (primarily cohort studies)
Information bias-Investigators who know exposure status may be more or less likely to ascertain the outcome (diagnostic bias)

40
Q

Fix for info bias

A

BLINDING of all personnel, investigators, and subjects to the exposure status of the subjects

CAN ONLY FIX BIAS IN DESIGN STAGE
or after with mv but then must measure bias

41
Q

Cohort Studies Adv (4)

A

good when exposure is rare,
can minimize selection and measurement bias,
can directly determine incidence rate and risk,
can look at multiple outcomes from single exposure

42
Q

Cohort studies Disadv (5)

A 
inefficient for rare outcomes
Needs large sample
long time to complete
Loses to follow up
Expensive
potential ethical issues
43
Q

What test should i do for prevalence?

A

Cross sectional

44
Q

What test should i do for risk of harm

A

cohort, cross sectional

45
Q

tWhat test should i do for treatment or prevention

A

RCT, Cohort, case-control

46
Q

prognosis

A

cohort

47
Q

screening

A

rct, cohort, case control

BMS I (30 decks)

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