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Research Methods in Health > Week 05 > Flashcards

Week 05 Flashcards

1
Q

Meta means…

A

beyond

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2
Q

What does a meta-analysis do….?

A

summarises results, improves precision of estimates of effects in population

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3
Q

Do all systematic reviews have meta-analyses?

A

No

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4
Q

______ review is the traditional literature review where author selects, reads and summarises without systematic process

A

narrative

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5
Q

A narrative review has risk of ___

A

bias (unreliability)

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6
Q

Which is more reliable, narrative or systematic review?

A

systematic

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7
Q

What are some disadvantages of systematic reviews/meta analysis ?

A
  • Cant review information that isn’t there
  • Can’t improve on poor quality information
  • May be difficult to validly combine statistical results from studies with different methods
  • Many systematic reviews give open finding (inconclusive) because sufficient high quality studies are lacking
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8
Q

A ____________ is a statistical method of combining results from multiple studies

A

meta-analysis

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9
Q

“pooled effect size” is a _____ result combining samples from multiple studies

A

single

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10
Q

Do larger or smaller samples provide more precise estimates?

A

Larger (more information)

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11
Q

List reporting biases affecting whether research findings are published at all (4)?

A
  • Publication bias: unfashionable research topics may miss out on publication
  • Time lag bias: rapid or delayed publication of results
  • Duplicate publication bias: the same research findings published in more than one article; also known as “salami slicing”
  • Outcome reporting bias: marked preference for studies with “significant” results; non-significant may be just as important
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12
Q

List biases affecting whether report included in review (4)?

A
  • Citation bias: whether the report appears in a reference list affects its chance of being spotted
  • Database inclusion bias: article not in database is harder to find
  • Language bias:
    preferences for studies in english
  • Personal biases of researchers doing the review
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13
Q

Funnel plot shows effect size by ____ size

A

sample

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14
Q

Bias against trials with small samples and negative/positive effects?

A

negative

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15
Q

If no publication bias, funnel plot will look symmetrical or asymmetrical?

A

symmetrical

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16
Q

Heterogeneity = ??

A

difference or diversity

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17
Q

Can clinical heterogeneity can cause statistical heterogeneity ?

A

Yes

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18
Q

Appraising systematic reviews: Validity of the methods used in the review

A
  • Clearly focussed question with clear eligibility criteria
  • High quality, relevant studies
  • Assessment of bias in the studies
  • Results combined across studies, but only if reasonable to do so
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19
Q

Appraising systematic reviews: Results of the review

A
  • Overall results of the review are presented

- Results are sufficiently precise

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20
Q

Appraising systematic reviews: Relevance of the results to your clinical practice

A
  • Outcome considered from the practitioners perspective

- Applicability of results to your own target population

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21
Q

What is ecological fallacy?

A

“what applies to the group, will also apply to the individual”

  • not sound concept
  • Internal validity threat
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22
Q

Value of systematic reviews to practitioners depend on (2)?

A
  • Availability and quality of primary studies for review

- Methods used to conduct the review

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23
Q

Meta-analysis estimates overall statistical effect size

A
  • Effectively increases the sample size, leading to higher precision
  • Feasibility affected by heterogeneity among studies
  • Can identify bias in individual studies
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24
Q

Standard review process applies to quantitative research

A
  • Strong emphasis on clinical trials but observation studies eligible
  • Qualitative research developing alternatives - meta synthesis
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25
Systematic reviews can/can't be affected by same biases as primary studies and biases specific to systematic reviews (cannot improve on original evidence quality --> heterogeneity is a risk)
can
26
Accidental, chance differences between same means and population average can lead to the risk of the researchers wrongly believing that sample accurate for whole population ---> this is where ___ ____ comes in
inferential statistics
27
Rarely possible to get complete data from population (impractical, extensive, instead researchers rely on _____ drawn from the population---> therefore, most quantitative research is at risk of sampling error)
samples
28
Descriptive statistics describe the sample....?
mean, mode, median, SD, min, max, range amount etc
29
How to sample results generalise beyond the sample affects the ___ validity
external
30
Population parameters (statistics) =
measurement or results for populations (means, SD, median numbers ratio etc)
31
Inference =
conclusion based on information (see smoke --> information, conclude there is a fire --> inference)
32
Inferential statistics enable conclusions (inferences) about _____ when only _____ data is available
populations, sample
33
Inferential statistics deal with ______ information
uncertain
34
______ is a prediction about what a result will be before the data is analysed or even collected
hypothesis
35
Hypotheses are exploratory or descriptive?
descriptive
36
Choosing hypotheses after inspecting the data is bad science... is like
asking a question after finding the answer
37
Are hypotheses proved and disproved?
No, they are either consistent or inconsistent
38
Null hypothesis is _____ the hypothesis
against
39
Null hypothesis is called H___
H0 (against hypothesis)
40
Alternative hypothesis is ___ the hypothesis
for
41
Alternative hypothesis is H___
H1 (For hypothesis)
42
Hypotheses are usually state or implied?
Implied
43
A _____ hypothesis is something that does not happen, no effect, treatment does not work, effect size = 0 (no difference between groups)
null (H0)
44
A _____ hypothesis is something that does happen, is effect, treatment works, effect size is NOT 0 (there IS a difference between groups)
alternative
45
Is a non-zero effect the same as "treatment works"... explain why
No, because it does not state the direction (could harm or benefit pt, AND doesn't account for minimal significance)
46
Equivalence is ________ hypothesis
nondirectional
47
Equivalence/nondirectional hypothesis are ____ interesting because we want to find benefit but the default statistical significance test
rarely
48
Superiority - directional hypothesis, H0 & H1:
- H0: treatment is not superior = does not have a larger beneficial effect than control - H1: Treatment is superior = does have a larger beneficial effect than control
49
Equivalence - nondirectional hypothesis, H0 & H1:
- H0: treatment and control have equal effects, no difference - H1: Treatment and control have non-equal effects, a difference in either direction - H1: goes either way, treatment better OR worse than control
50
Non-inferiority - directional hypothesis, H0 and H1:
- H0: treatment is "not unacceptably worse" than control - H1: treatment is unacceptably worse than control (common but questionable for EBP)
51
Hypotheses are about ______, not samples
populations
52
Hypotheses are for making ______ about populations based on sample data
inferences
53
Inference is a conclusion (about the ______) based on information (from the ____)
population, sample
54
Method to test inferences is ___ _____ that use sample data to infer beyond sample
inferential statistics
55
Inferences from sample to population are _____ --> thats why inferential statistics deals with it
uncertain
56
Qualitative research typically ____ hypotheses
avoids
57
H0 null hypothesis goes with statistical non-significance p ___ .05
> (greater than) | - zero effect
58
H1 alternate hypothesis goes with statistical significance p ___ .05
< (less than) | - non zero
59
If p < .05, ____ than 5% chance of sample effect if H0 is true
less (unlikely data)
60
If p < .05, ____ than 5% chance of sample effect if H0 is true
more (likely data)
61
Type 1 error...?
H0 is falsely rejected when p < .05 | - accidental error not calculation error
62
Type 2 error...?
H0 is falsely retained when p > .05
63
Limitations to hypothesis testing
- Clinicians want to know HOW WELL intervention works, not whether effect is zero - H1 "non zero" not informative for EBP (if rejected, all we know is data is unlikely true, what use is that?)

Research Methods in Health (12 decks)

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