Experimental Research Methods Flashcards
0
Q
grouped frequencies?
A
every value between and including first and last value
eg. 0-9, 10-19, 20-29
1
Q
stratified random:
A
groups first formed to ensure even representation of groups
M&F/race
2
Q
relative frequency?
A
percentage of all elements that fall within each class interval
frequency / sample size
3
Q
cumulative frequency?
A
percentage of distribution that lies in or below that particular group
4
Q
mode:
A
most frequent observation
5
Q
median:
A
mid point of the distribution (50th percentile)
6
Q
mean
A
arithmetic average
7
Q
what is a deviation score?
A
element - mean
8
Q
how do you calculate variance?
A
mean of the SQUARE of all deviation scores
variance = sum (X - mean)^2 / number of elements in population
9
Q
what is different about sample variance?
A
divide by sample size - 1
instead of just normal sample size
10
Q
what is the standard deviation?
A
the square root of the variance
11
Q
what % of distribution falls within 1 standard deviation?
A
68%
12
Q
what % of distribution falls within 2 standard deviations?
A
95%
13
Q
what % of distribution falls within 3 standard deviations?
A
99.7%
14
Q
what % of distribution falls ABOVE or BELOW 2 standard deviations?
A
95% within 2 standard deviations
therefore 5% above and below
or 2.5% below, and 2.5% above
15
Q
what % of distribution falls below 1 standard deviation?
A
well 68% within 1 standard deviation
and 16% below -1 standard deviation
68+16 = 84
16
Q
what is the standard deviation a measure of?
A
measure of variability
17
Q
how do you calculate SEM - Standard Error of the Mean
A
standard deviation / square root of n
18
Q
what is the null hypothesis?
A
this hypothesis you assume to be true
Ho = whatever you’re researching has NO effect -> no difference in mean
19
Q
what is the alternate hypothesis?
A
Ha or H1 = whatever you’re researching does have an effect -> difference in mean
20
Q
at what value do you reject the null?
A
if you get a p value of < 0.05
21
Q
What is the P-value?
A
- “probability” value
- % under the curve converted to decimal
eg. 0.3% under curve(p-value), 0.002 probability value
22
Q
what is a type 1 error?
A
error of rejecting the null hypothesis even through it is true
23
Q
what is a type 2 error?
A
failing to reject the null hypothesis, when the alternate hypothesis is actually true
24
what is degrees of freedom and how is it calculated?
expression of sample size
df = n - 1
25
how do you calculate chi-square?
sum of (observed - expected)^2 / expected
26
aims of medical research?
- cure disease
- prevent
- improve productive lifespan
- save $$ from health cost
27
what are the governing principles for the Australian code for the care and use of animals for scientific purpose?
3 R's
Replacement
Reduction
Refinement
28
describe "replacement" principle:
- ethical animal conduct
Replacement = methods that permit a given purpose of an activity or project to be achieved without the use of animals
eg. use of human instead - they can give consent for the most part
29
describe "reduction" principle:
- ethical animal conduct
methods for obtaining comparable levels of info from the use of fewer animals in scientific procedures or for obtaining more into from the same number of animals
eg. use pre-existing data
30
describe "refinement" principle:
- ethical animal conduct
methods that alleviate or minimise potential pain and distress, and enhance animal wellbeing
eg. allow animals to "acclimatise" to new environment and equiptment
31
levels of randomised control bias:
1 - systematic reviews of RCTs
2 - one RCT
3 - pseudo-randomised controlled trial
3.2 - comparative study with concurrent controls
3.3 - comparative study without concurrent controls
4 - case-series
32
describe the structure of a scientific study write up?
```
abstract
intro
methods
results
discussion
references
```
33
describe prediction by interpolation:
when dosage lies within tested range
34
describe prediction by extrapolation:
new dosage outside original range
35
steps in experimental process?
1) research question
2) hypothesis
3) data analysis
4) conclusion
36
how can we typically calculate the 95% Confidence Interval?
SEM x z-score
z-score for 95% confidence = 1.96
37
what can be assumed about the 95% Confidence Interval if the P<0.05?
the 95% confidence interval will not contain a zero
38
what does the P-value allow you to answer?
if there is no correlation between the 2 variables, what is the chance of observing a correlation as far from zero as we have observed, by chance(random sampling) alone?
39
what does placebo stop people from doing?
stops them hunting around for another treatment because many may believe they have the treatment
40
pseudo-random
kinda random but not, you can figure out the pattern
| like dates of birth, days of the week
41
what is the null hypothesis:
whatever you're researching has NO effect
| -> no diff. in mean
42
steps of hypothesis testing?
1) state the Ho and Ha
2) select decision criteria (P<0.05)
3) establish critical values (direction & df)
4) draw random sample, calculate mean
5) calculate S & SEM
6) calculate t-statistic for sample mean
7) compare t with critical values -> reject or retain the null hypothesis
43
what could increase the power of an experiment?
- eliminating inter-subject variation (eg. age)
- increased sample size
- minimising instrument errors
44
define knowledge translation
the synthesis, exchange & ethically sound application of knowledge by relevant stakeholders to accelerate the benefits of global and local innovation in strengthening health systems and advancing peoples health
45
what is knowledge creation?
primary research
46
what is knowledge distillation?
creation of systematic reviews/guidelines
47
what is knowledge dissemination?
appearances in journals and presentations
48
what people are involved in knowledge translation?
health care professionals/providers(clinicians)
patients
managers
policy makers
49
identify and briefly discuss 4 factors that are known to influence how easily research evidence is translated into policy or practice:
1) what: is being implemented, characteristics of implementation
2) who: characteristics of target groups,
3) where: features of the context in which you are attempting to implement
4) how: process used to facilitate implementation
eg. generally need tailored interactive and multi-faceted approach
50
what 3 assumptions underpin the knowledge translation metaphor?
1st: 'knowledge' equates with objective, impersonal research findings
2nd: it is useful to conceptualise a 'know-do' gap between scientific facts and practice
3rd: practice consists of a series of rational decisions on which scientific research findings can be brought to bear
51
why does the 'know-do' gap exist?
1) lack of standardised and up to date practice guidance
| 2) need for a better design and more effective use of electronic information system
52
in terms of qualitative studies what could be some patient level factors?
- perceived benefits and drawbacks
- ability to self-manage(if applicable)
- acceptability of equipment used,
- desire/demand for extra support/technology/
53
in terms of qualitative studies what could be some clinical level factors?
- personal experience
- politics and personalities
- trust in evidence base
54
in terms of qualitative studies what could be some organisation level factors?
- service investment requirements
| - impact on non-pump population
55
in terms of qualitative studies what could be some system level factors?
- commissioning pump services
| - who pays ad how
56
language and terminology likely to be used to describe the process of moving research into policy and practice:
knowledge translation, mobilisation, utilisation, exchange, transfer
implementation science, translational science, research utilisation
57
define efficacy:
ability of an intervention to produce results under ideal conditions
eg. RCT with well staffed & motivated patients
58
define effectiveness:
ability of intervention to produce results in general use
59
define mobilisation:
moving available knowledge into active use
60
define utilisation:
extent to which potential access is converted into realised access
61
what is implementation science?
study of methods to promote the integration of research findings and evidence into healthcare policy and practice
62
how can qualitative research help with decision making?
1) directing and informing policy and program development
2) assisting in program design
3) considering individual health decisions, actions, impacts
4) directing and informing policy and program evaluation
63
3 considerations - in place of experiments in the universe of health research:
1) efficacy and effectiveness
2) questions of meaning
3) public health approaches
64
what is PICO?
a framework for evidence-based decision process - study design
helps you answer clinical questions using research data
65
what does PICO stand for?
```
P = patient/populaiton
I = intervention
C = comparison/control
O = outcomes
```
66
define a systematic review:
a review in which there is..
- comprehensive search for relevant studies on a specific topic
- studies identified are then appraised
- and synthesised according to a pre-determined and explicit method
67
meta-analysis:
- quantitative analysis of results
- putting available studies together increases statistical power
=> decreases likelihood of type 1&2 errors
- generalisability of results improved by combing studies
68
when do you use a one sample z-test?
when there is just 1 mean and you know the standard deviation
69
when do you use a one sample t-test?
when there is just one mean but you DO NOT know the standard deviation
70
when do you use a 2 sample t-test?
when there are 2 means
71
matched/paired/pooled t-test?
used when 2 measurements on each subject
72
when do you use chi-square test?
OBSERVED
| EXPECTED values
73
what is regression/correlation useful/often used for?
to predict the value of one variable based on another variable
74
what is the equation of a line
y = mx + b
Y = b0 + b1*X
```
b0 = intercept
b1 = slope
```
75
how do you calculate slope?
y = y2 - y1 / x2 - x1
76
requirements of a well designed study
1) absence of bias
2) sufficient power
3) exploration of range of applicability
4) keep it simple: minimise chance of making mistake
5) amenable to statistical analysis
77
why do experiments with/in humans?
- results applicable "human are humans"
- can directly study the actual disease/problem(model not the same)
- subjects can describe how they're feeling
- humans can consent to participate
- test real life situations
- can be cheaper
78
why do animal experiments?
- test causality or establish mechanisms
- eliminate variation(genetic, environmental), confunding
- some experiments are impossible in humanseg.killing to collect tissue
- establishing safety before human
- no problems with adherence to protocol
- get enough subject
79
what different categories of people does an animal ethics committee consist of?
A: vet
B: recent/current experience in use of animals for scientific purposes
C: RSPCA/animal welfare
D: random person, generally older person
E: person looking after animals within institution
80
when using animals you need to consider?
3 R's
Replacement: achieved without use of animals
Refinement: minimise pain, enhance wellbeing
Reduction: fewer animals, or same info from same amount of animals
81
what are the NHMRC levels of evidence for interventions?
I: systematic review trial
II: one RCT
III: pseudo-RCT
III-2: comparative study with concurrent controls
III-3: comparative study withOUT concurrent controls
IV: case-series
82
what is randomisation?
allocation of treatment to trial participants based on chance
83
what is selection bias?
good generation of random sequence that cannot be determined by anyone(concealment of allocation)
*before trial starts
84
what is performance bias?
blinding of participants and personnel
| *once trial has started
85
what is attrition bias?
maintaining blinding of participants especially
*avoid placebo group sourcing treatments else where
86
what is detection bias?
blinding of outcome assessors especially
* avoid favouring of certain participants
87
what is reporting bias?
select the good results to report, or conflict of interest
88
what are the 4 pillars of ethical research?
1) merit & integrity
2) justice
3) beneficience
4) respect to persons
89
describe pillar 1: merit and integrity of ethical research:
- honesty in research
| - ensuring legitimate search of knowledge
90
describe pillar 2: justice of ethical research:
- do not "lie"
- selection, recruitment, exclusion and inclusion of research participants must be reasonable
- fair distribution of benefits and burdens
91
describe pillar 3: beneficence of ethical research:
- minimise risk of harm to participants
| - offers benefits to society
92
describe pillar 4: respect to persons of ethical research:
recognition of their intrinsic value, respect privacy, confidentiality
93
what is the most important pillar of ethical research?
respect to persons!
94
describe informed consent:
voluntary, based on sufficient info, adequate understanding of research and implications of participation
*basically no coerce - cannot black mail/pressure/manipulate people to do shit
95
what does it mean if the confidence interval line on a forest plot crosses the mid line?
if the confidence interval line of a study crosses the mid line the results of the study are NOT statistically significant
96
in a forest plot what does the size of each diamond show?
the size of each data point or diamond shows sample size of each study
97
when studies are put into funnel plot what does it show?
it shows presence of performance bias within the study
98
in a funnel plot what is along the x axis?
favours treatment ------------------------------ favors control
99
in a funnel plot how would you identify the presence of bias?
when there is a big gap
- has been in right bottom in all diagrams i've seen
100
name the major types of variables and their sub-topics:
```
categorical= regular(M/F, nationality) & ordinal(categories ascending & descending)
numerical= continuous -> interval, ratio & discrete -> counts(# of kids)
```
101
example of catagorical regular data:
M/F
marital status
nationality
102
example of categorical ordinal:
things that can be placed in ascending or descending order
103
what type of data would age be?
numerical continuous ratio
104
what type data is size?
categorical ordinal
105
what type of data is sex?
categorical regular
106
what type of data would the number of kids be?
numerical discrete
107
what hypothesis do you assume to be true?
null
108
2 possible consequences for not blinding?
1) performance bias - blinding of patients & personnel
| 2) attribution bias - maintaining patient blinding to prevent drop out and seeking treatment else where
109
if by chance the control group of a study contained bias eg. more horrible children or older average age how would this influence interpretation of results?
..what statistical test could analysis this accurately?
control would have higher or lower dependent variable at baseline
repeated measures analysis
-> looks at change from baseline in each group
110
in a question where 2 measures are taken from the same subject what statistical test is likely to be used?
paired t-test
111
in a question where there are 2 means what statistical test is likely to be used ?
2 sample t test
112
in a question where there are 2 cohorts with no association to each other in a study what statistically test is likely to be used?
chi-squared
113
what is a major purpose of random assignment in a clinical trial?
to help ensure that study subjects are representative of the general population
114
how do you find the mean if the study is paired?
paired means 2 measures are taken on the same subjects
therefore you must find the mean difference for each participant
eg. post-treatment x - pre-treatment x
then sum the differences and divide by sample size = sample mean
115
what is the difference between df with 2 means?
(n treatment + n control) - 2
116
if people are recruited from different places how does this effect the results of the trial?
it shouldn't effect the results of the trial as long as participants are properly randomly allocated
(random allocation prevents selection bias)
117
what kind of bias is it when people seek other treatment?
performance bias
118
what kind of bias is it when participants have a lack of interest?
attribution bias
119
how would you go about answering this question?
| "Is attrition bias likely to be a problem in this study?"
think of all the reasons why participants could become demotivated and drop out of the study
