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EXAM > Stats, Epidem, EBM 2.5 > Flashcards

Stats, Epidem, EBM 2.5 Flashcards

1
Q

A type of study with random allocation to intervention/control group but can be limited by practical/ethical problems

A

RCT

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2
Q

observational & Prospective study e.g. Framingham heart study?
What is the usual outcome measure?

A

Cohort study - e.g. follow a cohort who have all had exposure to an agent, to see how many develop an outcome
- measure Relative Risk

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3
Q

observational & Retrospective study?
what is the usual outcome measure ?
benefits?

A

Case-control study e.g. match cases with controls, collect data & identify possible causal agents

  • measure Odds ratio
  • inexpensive, quick results, useful for rare conditions
  • but prone to confounding & Recall bias
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4
Q

A study that provides a snapshot in time?

A

X-sectional study (or prevalence study)

- weak evidence of cause & effect

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5
Q

What determines what type of significance test is used?

A

whether data is parametric (can be measured, usually normally distributed), or non-parametric

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6
Q

Examples of parametric tests for:

  • paired/unpaired data?
  • correlation?
A
  • student’s t-test - paired (single group) or unpaired

- Pearson’s product-moment coefficient - correlation

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7
Q

Examples of non-parametric tests for:

  • unpaired data?
  • correlation?
  • comparing 2 sets of observations on a single sample?
  • comparing proportions/percentages?
A
  • unpaired: Mann-Whitney U test
  • correlation: Spearman, Kendall rank
  • Wilcoxon signed-rank test (2 observations on 1 sample)
  • chi-squared test (%)
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8
Q

What is pre-test probability?

A
  • proportion of people with the target disorder in the population at a point in time or time interval i.e. point/period prevalence
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9
Q

What is post-test probability?

A
  • proportion of pts with the test result who have the target disorder (think pp.)
    = post-test odds / (1+post-test odds)
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10
Q

What is pre-test odds?

A
  • odds the pt has a target disorder before the test is carried out
    = pre-test probability / (1 - pre-test probability)
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11
Q

What is post-test odds?

A
  • odds the pt has the target disorder after the test is carried out
    = pre-test odds X likelihood ratio
  • where the likelihood ratio for a +ve test result = sensitivity / (1 - specificity)
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12
Q

Null hypothesis is rejected when it is true i.e. showing a difference between 2 groups when it doesn’t exist - a false positive

A

Type I statistical error

  • not affected by sample size
  • increased if no of end-points are increased
  • determined against a preset significance level (alpha)
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13
Q

Null hypothesis accepted when it is false i.e. failing to spot a difference when one exists - a false negative

A

Type II statistical error

  • probability of making this error = beta
  • determined by both sample size & alpha
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14
Q

What is the power of a study?

A

The probability of correctly rejecting the null hypothesis when it is false i.e. probability of detecting a statistically significant difference
= 1 - beta (prob of a type II error)
- can be increased by increasing the sample size

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15
Q

% of values that lie within 1 SD of the mean

A

68.3%

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16
Q

% of values that lie within 2 SD of the mean

A

95.4%

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17
Q

% of values that lie within 3 SD of the mean

A

99.7%

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18
Q

What is standard deviation and it’s calculation

A
  • a measure of how much dispersion exists from the mean

SD = square root (variance)

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19
Q

How to calculate the variance?

A

“mean of the squares - square of the mean”

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20
Q

What is and how to calculate the standard error of the mean?

A

= SD / square root (no. of values)

  • a measure of the spread expected for the mean of the observations
  • SEM gets smaller as the sample size (n) increases
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21
Q

Phase I of clinical trials?

A
  1. detemines pharmacokinetics & pharmacodynamics & side-effects prior to larger studies
    - on healthy volunteers
22
Q

Phase II of clinical trials?

A
  1. assess efficacy & dosage - involves small no of pts affected by a particular disease
    IIa: assesses optimal dosing
    IIb: assesses efficacy
23
Q

Phase III of clinical trials?

A
  1. assesses effectiveness

- typically involves 100-1000s of people, often part of RCT comparing new & established treatments

24
Q

Phase IV of clinical trials?

A
  1. Postmarketing surveillance - monitors for long-term effectiveness & side-effects
25
Q

What are funnel plots used to demonstrate?

A

Existence of publication bias in a meta-analysis

  • horizontal axis: treatment effects
  • vertical: study size
26
Q

What is bias?

A

situation in a trial where 1 outcome is systematically favoured

27
Q

What is selection bias?

A

Error in assigning individuals to groups leading t odifferences which may influence outcome

  • Sampling: subjects not representative of the population
  • Volunteer: subjects more/less likely to volunteer
  • Non-responder: e.g. those who smoke less likely to respond to smoking survey
  • Loss-to-follow-up bias
  • Prevalence/Incidence/Neyman bias: when a study Ix a condition characterised by early fatalities/silent cases
  • Admission/Berkson bias: cases & controls in a hospital study different as exposure to risk & disease occurrence increases likelihood of admission
  • Healthy worker effect
28
Q

What is recall bias?

A

Difference in accuracy of recollections retrieved by study participants e.g. due to whether they have a disorder or not
- problem in case-control studies

29
Q

What is publication bias?

A

Failure to publish results from valid studies, often as they showed a negative/uninteresting result
- important in meta-analysus where studies showing negative results may be excluded

30
Q

What is Work-up/Verification bias?

A

In studies which compare new Dx tests with gold standards:

  • clinicians may be reluctant to order the gold standard unless the new test is positive (eg if the gold standard is invasive e.g. tissue Bx)
  • can really distort results of a study, altering specificity & sensitivity
  • sometimes can’t be avoided
31
Q

What is expectation bias (Pygmalion effect)?

A
  • observers may sunconsciously measure/report data in a way that favours the expected study outcome
  • problem in non-blinded trials
32
Q

What is the Hawthorne effect?

A

Describes a group chaging its behaviour due to the knowledge it is being studied

33
Q

What is late-look bias?

A

Gathering info at an inappropriate time e.g. studying a fatal disease many years later when some pts may have died alreadu

34
Q

What is procedure bias?

A

When subjects in different groups receive different treatment

35
Q

What is lead-time bias?

A

When 2 tests for a disease are compares, the new test diagnoses the disease earlier, but there’s no effect on the outcome of the disease

36
Q

What is selection bias?

A

Error in assigning individuals to groups, leading to differences which may influence outcome

  • Sampling: subjects not representative of population, e.g. may be due to volunteer bias, non-responder bias
  • other examples inc loww to follow-up, prevalence/incidence aka Neyman, admission aka Berkson, healthy worker effect etc
37
Q

What is information bias?

A

When measurement of info differs among study groups

- e.g. recall bias, reporting bias, Dx bias, Hawthorne effect, errors in measurement

38
Q

What is confounding bias?

A

Distortion of exposure or disease relation by some other factor

39
Q

What is detection bias?

A

Outcomes are sought after, more in 1 group than another

40
Q

What is the p value?

A

= probability of obtaining a result by chance at least as extreme as the one actually observed, assuming that the null hypothesis is true
= the chance of making a type I error

41
Q

What is a null hypothesis? H0

A

It sates 2 treatments are equally effective (hence negatively phrased)

42
Q

What is a significance test?

A

it uses the sample data to assess how likely the null hypothesis is to be correct

43
Q

Level of evidence Ia?

A

from meta-analysis of RCTs

44
Q

Level of evidence Ib?

A

from at least 1 RCT

45
Q

Level of evidence IIa?

A

from at least 1 well designed controlled trial (not randomised)

46
Q

Level of evidence IIb?

A

from at least 1 well designed experimental trial

47
Q

Level of evidence III?

A

evidence from case, correlation & comparative studies

48
Q

Level of evidence IV?

A

evidence from a panel of experts

49
Q

study design Grade A?

A

based on evidence from at least 1 RCT i.e. evidence Ia/Ib

50
Q

study design Grade B?

A

based on evidence from non-RCTs i.e. evidence IIa/IIb/III

51
Q

study design Grade C?

A

based on evidence from a panel of experts i.e. evidence IV

EXAM (21 decks)

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