Critical Numbers Flashcards
1
Q
What is a case control study?
A
identify individuals with a particular outcome
retrospectively look back to see if they had the risk factor in question
non randomised
observational
retrospective
2
Q
advantages of case controls
A
good for rare outcomes
fast as uses past data so no need for long follow up
cheaper
3
Q
disadvantages of case controls
A
difficult to prove causation
prone to biases
not ideal for rare exposures
4
Q
what is a cross sectional study?
A
collect data from many individuals at a moment in time
non randomised
observational
5
Q
advantages of cross sectional studies
A
can assess multiple exposures/ outcomes
relatively quick
cheap
6
Q
disadvantages of cross sectional studies
A
not ideal for rare exposures/ outcomes
susceptible to bias
cannot prove causality
7
Q
what is a RCT
A
randomly allocate participants to different interventions and follow up
experimental
prospective
8
Q
advantages of RCTs
A
gold standard - randomisation reduces potential for confounding
can determine causality
can reduce bias via control and blinding
ABC of strengths - allocation at random, blinding, control
9
Q
disadvantages of RCTs
A
randomisation can be unfeasible or unethical when evaluating harmful exposures
require expert management and oversight for high risk interventions
resource intensive and expensive
strict eligibility criteria may mean sample not representative
10
Q
what is a cohort study
A
the individuals in the sample may or may not have the exposure in question
after a period of follow up, the number of people who develop an outcome are recorded
non randomised
observational
typically prospective
follow up over time
11
Q
advantages of cohort studies
A
useful when random allocation not possible
can work on rare exposures
can examine multiple outcomes
12
Q
cons of cohort studies
A
long follow up
not ideal for rare outcomes
can be expensive
13
Q
what is an ecological study
A
the unit of observation is the group rather than the individual e.g electoral ward, country
14
Q
pros of ecological studies
A
large scale comparisons
can quantify geographical or temporal trends
15
Q
cons of ecological studies
A
ecological fallacy
cannot make inference at the individual level from data at the group level
16
Q
what is a systematic review?
give one strength and one weakness
A
research article in which existing evidence on a topic is systematically identified, appraised and summarised according to predetermined criteria
transparent, systematic methods make the process replicable
publication bias
17
Q
what is a meta-analysis?
A
statistical synthesis of the evidence
effect sizes from each individual study are combined to create a single overall effect size
shown on forest plot
18
Q
what is variation between studies called?
A
heterogeneity
quantified using a Q or I^2 statistic
19
Q
describe the hierarchy of evidence from top to bottom
A
systematic review/ meta analysis
RCT
cohort study
case control study
cross sectional study
case study/ expert opinion/ anecdote
20
Q
what is a sample
A
a subset of individuals from a population (should be representative of the population of interest, but isn’t always!)
21
Q
what are generisable results?
A
representative of the population of interest
22
Q
when is a sample biased?
A
certain subgroups of the population are over/ underrepresented in the sample
23
Q
what is bias?
A
imperfections in the research process cause findings to deviate from the truth
24
Q
what is sampling bias?
A
sample does not represent population of interest
25
what is recall bias?
inaccurate recall of past events/ exposures/ behaviours
26
what is information bias?
incorrect measurement e.g miscalibrated machine
27
what is the Hawthorne effect?
participants change their behaviour when they know they are being watched
28
attrition bias
differential dropout from studies e.g sicker participants drop out so the outcome is only measured on healthier participants
29
what are confounders
variables that obscure the real effect of an exposure on an outcome
related to both exposure and outcome
30
what is the most important part of a study?
design!
31
what is an experimental study
researchers have intervened in some way
32
what is an observational study?
researchers have observed without intervening
33
what are the three divisions of observational studies?
retrospective, cross sectional and prospective
34
what is a retrospective study?
looking back in time
35
what is a cross sectional study?
single snapshot in time
36
what is a prospective study?
following up over time
37
what is simple random sampling?
each member of the population has an equal probability of being selected
38
what is an ecological study?
unit of observation is the group rather than the individual
39
give 5 types of sampling
random, systematic, quota, cluster, stratified
40
describe random sampling
using a random number number generator
41
describe systematic sampling
researchers select members of the population at a regular interval
42
describe quota sampling
non-probability sampling method that relies on the non-random selection of a predetermined number or proportion of units
43
describe cluster sampling
divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample
44
describe stratified sampling
researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment). Once divided, each subgroup is randomly sampled using another probability sampling method.
45
give some examples of bias
sampling, recall, social desirability, information, volunteer, selection, lead time bias, length time bias
46
what is sampling bias?
occurs when some members of a population are systematically more likely to be selected in a sample than others
47
what is recall bias?
systematic error that occurs when participants do not remember previous events or experiences accurately or omit details
48
what is social desirability bias?
respondents conceal their true opinion on a subject in order to make themselves look good to others.
49
what is information bias?
key study variables are inaccurately measured
50
what is volunteer bias?
arises in any research study in which participants choose if they want to be part of the sample
51
what is selection bias?
distortion in a measure of association (such as a risk ratio) due to a sample selection that does not accurately reflect the target population
52
which two types of biases are associated with screening?
lead time and length time biases
53
what is lead time bias?
occurs when a disease is detected by a screening or surveillance test at an earlier time point than it would have been if it had been diagnosed by its clinical appearance
54
what is length time bias?
overestimation of survival duration due to the relative excess of cases detected that are asymptomatically slowly progressing, while fast progressing cases are detected after giving symptoms
55
what are confounding factors?
related to outcome and exposure
56
what is critical appraisal?
the process of systematically examining research to judge its trustworthiness, and its value and relevance in a particular context
the process of assessing and interpreting evidence by systematically considering its validity, results and relevance to your own context
57
what is evidence based medicine?
the conscientious explicit and judicious use of current best evidence in making decisions about the care of individual patients
58
what is reliability?
the overall consistency of a measure
a measure is said to have a high reliability if it produces similar results under consistent conditions
59
what is validity?
extent to which a concept is accurately measured
60
what is internal validity?
accurately measuring those within the trial
61
what is external validity?
generalisable outside the trial
62
what are the 4 components/ questions of CASP?
1. is the basic study design valid for a randomised controlled trial?
2. was the study methodologically sound?
3. what are the results?
4. will the results help locally?
63
key considerations of RCTs
randomisation
- were key confounders included to reduce bias
- was the allocation sequence concealed
attrition
- exclusion bias
- drop out or lost to follow up
confidence in results
- are the results clinically important
- do the effect estimates include confidence intervals
64
what is PICO and what does it stand for?
a way of generating research questions
P - population
I - intervention
C - comparator
O - outcome
65
what is a variable
anything that varies within a dataset
66
what are the types of variables?
categorical, numerical
67
what are the types of categorical variables?
binary - only two categories e.g yes/ no
ordinal - categories with natural order e.g social class
nominal - categories with no natural order e.g hair colour
68
what are the types of numeric variables?
discrete - observations can only take certain numerical values
continuous - observations can take any value within a range (the only restriction is the precision of the measurement tool)
69
what is the mean?
add all the numbers in a data set and divide by the number of values
70
what is the median?
found by ordering the data points and selecting the middle number
71
what is the mode?
most frequent number
72
which measures of central location are the same in a normal distribution?
mean, median and mode
73
what is the standard deviation?
describes the variation of observations in our sample around the mean
also need to know the equation
used if we want to create a normal or reference range
(spread of data, describes spread around mean)
74
how do we calculate standard deviation?
calculate difference between each observation and the mean
square them to make them positive
sum then
divide by the number of observations minus one
take the square root to reverse the earlier squaring
75
which quartiles give the central 50% range
interquartile range 25th to 75th centile
76
how do we find the interquartile range?
halve data
difference between median of first half and median of second half
77
what is the standard error?
quantifies the precision of an estimate of the mean value
standard deviation of the sampling distribution
also need to know equation
used when we want to create a confidence interval around a point estimate
(spread of means, estimates real mean)
78
what affects the standard error?
how variable the data is
sample size
79
how much data is within one, two and three standard deviations of the mean?
68%, 95%, 99.7%
80
what is skew?
data is not normally distributed
81
what would a negatively skewed bell curve look like?
what are the relative mean, median and mode?
peak is further to the RIGHT (seems unusual, but remember that the tail is on the negative side of the graph)
mode>median>mean
82
what would a positively skewed bell curve look like?
what are the relative mean, median and mode?
peak is further to the LEFT (seems unusual, but remember that the tail is on the positive side of the graph)
mean>median>mode
83
what is kurtosis?
vertical skew
84
for skewed distributions, do we use the mean or median?
median as it has half of the data points on each side
85
what is the IQR?
measure of spread
used in conjunction with median
expressed as UQ - LQ
used when data isn't normally distributed
86
what are confidence intervals?
range of values our population mean is likely to lie in
describes variability around data
87
how do we calculate the 95% confidence intervals?
mean +- (1.96 x SE)
requires you to know the equation for standard error!
88
how to construct a box and whisker chart
median is middle line
next two lines outwards are LQ and UQ
boundaries are LQ - (1.5 x IQR) and UQ + (1.5 x IQR)
outliers represented by crosses
89
when are scatterplots used?
display 2 continuous variables
used to assess correlation and regression
90
what is risk and what range of values can it take?
number with an outcome divided by the total number
synonym for probability
0-1
91
what is the absolute risk difference?
the difference between 2 risks
92
what does the absolute risk difference give us?
the number needed to treat/ harm
this is the number of patients you need to treat to prevent one additional bad outcome
93
formula for number needed to treat/ harm
1/ARD
94
what is relative risk (risk ratio) and how is it calculated?
the ratio between two risks
divide one risk by the other
95
what does a risk ratio of less than one indicate?
lower risk
96
what does a risk ratio of more than one indicate?
higher risk
97
what are odds?
the number with an exposure or outcome divided by the number without
98
what is the odds ratio?
odds in one group divided by the odds in the other
99
what does it mean if there is an odds ratio of 1?
there is no between-group difference
100
why use odds over risk?
odds are symmetrical
the odds ratio for outcome Y is the inverse of the odds ratio for outcome not Y
risk ratios lack this symmetry
101
do case control studies estimate odds or risk?
odds
102
what is sensitivity and how is it calculated?
ability of a test to detect true positives
ability of a test to correctly identify individuals with the disease
number of true positives successfully identified / actual number of positives
103
what is specificity and how is it calculated?
ability of a test to successfully exclude negatives
ability of a test to correctly identify those who do not have the disease
number of true negatives successfully identified / actual number of negatives
104
what is positive predictive value and how is it calculated?
the proportion of people with a positive test who actually have the disease
number of true positives successfully identified/ number of positives identified in total
105
what is negative predictive value and how is it calculated?
the proportion of people with a negative test who are correctly excluded by the screening test
number of true negatives/ number of negatives identified in total
106
what is test accuracy and how is it calculated?
measures the ability of a test to detect a condition when it is present and detect the absence of a condition when it is absent
number of successfully identified negatives or positives/ total number of people tested
107
what is prevalence and how is it calculated?
proportion of people in a population who have a particular disease or attribute at a specified point in time
number of people who have the disease (including false negatives)/ total number tested
108
what are the two hypotheses?
null - H0 and alternative - H1
109
what is the significance level?
determines whether a result is statistically significant
also the probability we incorrectly reject the null hypothesis
110
what is the usual value of the significance level?
0.05
111
what does a p value indicate?
probability of obtaining result or a result more extreme if the null hypothesis is true
(probability result is due to chance)
112
when do we reject the null hypothesis?
when the p value is lower than the significance level
113
what do the confidence intervals indicate?
plausible range for a variable
precision of an estimation
statistical and clinical significance (although these are not the same)
114
what is the relationship between the significance of a result, the null value (0) and the confidence intervals?
a result is significant at the 5% level if the 95% confidence interval does not include the null value
a result is significant at the 1% level if the 99% confidence interval does not include the null value
and so on
115
for skewed distributions, do we use the mean or median?
median as it has half of the data points on each side
116
what percentage of data points lie within
a) one standard deviation of the mean
b) two standard deviations of the mean
c) three standards deviations of the mean
a) 68%
b) 95%
c) 99.7%
117
what is correlation?
measure of the linear relationship between variables
118
what letter represents the correlation coefficient?
r
119
what range of values can the correlation coefficient take?
-1 to 1
120
what is the difference between descriptive and inferential statistics?
descriptive statistics relate to the sample
inferential statistics relate to the population
121
what is the central limit theorem?
when taking repeat samples of a population and calculating the mean, the sample means will be normally distributed around the true population mean
122
what is the difference between standard deviation and standard error?
standard deviation describes the variation of observations in our sample
standard error quantifies the precision of an estimate of a population parameter
123
when do we use the standard deviation and when do we use the standard error?
standard deviation - create a normal or reference range
standard error - create a confidence interval around a point estimate
124
what is the difference between correlation and regression?
correlation quantifies the linear relationship between two numeric variables
order does not matter
regression allows one variable to be predicted from another
quantify associations between exposures and outcomes
order matters (e.g predict y from x)
can handle multiple predictors
125
what equation does regression take its form in?
y = a + bx (straight line graph)
126
what do each of the variables of the regression line mean?
y
a
b
x
y - variable being predicted (dependent variable)
a - y intercept of the regression line (the constant)
b - regression coefficient (gradient of the regression line)
x - the predictor (independent variable)
127
how can we tell if a factor is a significant predictor of another?
p value is less than significance level
128
what is the difference between uninvariable and multivariable regression?
univariable regression looks at one predictors
multivariable regression looks at multiple predictors
129
what are the advantages of multivariable regression?
there are often multiple predictors/ explanatory factors of a given outcome
can adjust/ control for confounders
make prediction based on a combination of risk factors
130
what are the 9 Bradford Hill criteria
strength of association - the stronger an association, the more likely it is to be causal
consistency - association shown across different studies in different locations, populations, using different methods
specificity - specific exposure-outcome relationship e.g asbestos and asbestosis
temporality - exposure must proceed outcome
biological gradient - dose response i.e increase in exposure = increase in outcome
plausibility - biological mechanism that would explain outcome development
coherence - compatible with existing theories
experiment - outcome altered with experimentation e.g reversible
analogy - similar cause-effect relationships established
131
what is epistemology?
involves knowledge claims and what we can assert about the world and limits of what can be known
132
what are the two main epistemological positions?
positivism and interpretivism
133
what is positivism?
about EXPLANATION - need for statical generalisation
key philosophy which underpins research in the natural and physical sciences
based on concepts such as
- objectivity
- scientific method
- empiricism
134
what is interpretivism?
about EXPLORING AND UNDERSTANDING - need for depth and context
not a single philosophical approach, but linked to several
hermeneutics - interpreting unique human activity
phenomenology - how individuals experience the world
the assumption is that social reality can only be understood through social constructions such as language, consciousness and shared meanings and understandings
does not predefine variables, but explores human sense making in naturalistic settings
135
what is the difference between methodology and method
method is a specific technique for data collection
methodology is the study of methods and refers to the strategy or approach to research
136
compare the two methodologies
quantitative
- deductive (theory testing)
- large random samples
- results as numbers and statistics
- emphasis on following original research plan
qualitative
- inductive (develop theory)
- small purposeful samples
- results as words and concepts
- flexibility of approach
137
give formats of qualitative data
interview transcripts
photographs
blogs
social media
138
what is the purpose of qualitative analysis?
provided interpretation of seemingly inexplicable activities e.g drug taking
very good at getting contradiction around an issue
provide general statements about relationships among categories of data
139
give examples of analysis of qualitative data
narrative, IPA, grounded theory
140
characteristics of qualitative research
natural context
non-manipulative
subjectivity/ reflexivity
141
are systematic reviews/ meta analyses primary or secondary evidence?
secondary
142
what are scoping/ narrative reviews?
summarise available research on a given topic
question may be broader
do not necessarily follow such strict, standardised, transparent methodology
less rigorous, more subjective and more prone to selection bias
143
what is a systematic review?
a research article in which existing evidence on a topic is systematically identified, appraised and summarised according to predetermines criteria
synthesises the available evidence on a given topic to answer a research question
144
why are systematic reviews top of the hierarchy of research evidence?
transparent, systematic methods make the process replicable
bias is addressed by assessing each individual study for bias
provide reliable estimates of intervention effects
145
steps of a systematic review
specify research question
develop search strategies and inclusion/ exclusion criteria
identify relevant studies
assess quality and risk of bias
extract data from each study
pool and interpret results
answer research question
146
what is a meta-analysis?
'the analysis of analyses'
statistical method for combining evidence from different sources
often used in systematic reviews
147
what type of graph shows a meta analysis?
forest plot
148
describe a forest plot
one row per study
the point estimate is shown as a square with size proportional to the size of the study
horizontal lines are confidence intervals
shows the measure of effect (for example, odds ratio)
solid vertical line indicates the lie of no effect (null). if an odds ratio has been used, the line of no effect is at the null value of 1
summary measure included - diamond shows the pooled estimate from the meta-analysis
149
what are fixed effect and random effects?
different approach to meta analysis
150
what is sensitivity analysis?
analysis to test the robustness of the findings of primary analysis - looks at the effect of assumptions or variations in approach
