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MFSRH Part 1 CM > Statistics > Flashcards

Statistics Flashcards

1
Q

What is incidence

A

Number of new cases emerging in a designated period and population

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2
Q

What is prevalence

A

Proportion of people in the entire population who are found to be with disease at a certain point in time

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3
Q

What is Sensitivity

A

True positive (correctly positive)

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4
Q

What is specifity

A

Correctly negative

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5
Q

What is efficacy

A

The effect of something under ideal or laboratory conditions

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6
Q

What does western blot detect

A

Identify proteins

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7
Q

What does northern blot detect

A

mRNA

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8
Q

What does southern blot detect

A

DNA

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9
Q

Describe a cohort study

A

Subjects with a risk factor are recruited.
Two groups are followed up, one with the risk and one without.

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10
Q

Other names for cohort study

A

Prospective or follow up

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11
Q

Name two observational descriptive studies

A

Case report and case series

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12
Q

Downsides of cohort studies

A

Expensive as can be long
Dropout can lead to bias

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13
Q

What is a case control study

A

Subjects who have the outcome (cases) are matched with those who do not (controls). All subjects are asked about past exposure to risk(s)

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14
Q

Other names for case control studies

A

Case comparison
Retrospective

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15
Q

Benefits of case control studies

A

Speedy
Useful when new diseases emerge

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16
Q

Drawbacks of case control

A

Recruiting matched controls
Rely on recall

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17
Q

What is a cross sectional study

A

The prevalence of an exposure and an outcome in a population at one point in time

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18
Q

Tools for reviewing effectiveness of cross sectional studies

A

GRACE, STROBE

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19
Q

What is an experimental study

A

The researcher intervenes in some way to measure the impact of a treatment

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20
Q

What makes a trial uncontrolled

A

Same treatment given to everyone

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21
Q

What makes a trial controlled

A

Subjects are given one of two treatments

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22
Q

What is the gold standard design for studying treatment effects

A

Randomised control trial

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23
Q

What is a crossover trial

A

Subjects receive one treatment then switch to another.

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24
Q

Benefits of crossover trial

A

Can be used to study rare diseases where lack of recruitment could make a trial underpowered.
Subjects are their own control

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25
Q

Downsides of a crossover design

A

Comparison takes place at two different points in time

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26
Q

What is a factorial trial

A

Assess the impact of more than one intervention

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27
Q

What is an audit

A

Aspects of service provision are assessed against a gold standard

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28
Q

What is a systematic review

A

Access and review of all pertinent articles in a field

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29
Q

What is a meta analysis

A

Combines results of several studies and produces a quantitative assessment

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30
Q

What is a pilot study

A

Miniature replica of the proposed trial

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31
Q

What is the benefits of a pilot study

A

Helps create efficient well designed studies. Increases successes, can show if a trial would be unable to recruit

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32
Q

What happens in phase 0 clinical trials

A

Microdose humans

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33
Q

What happens in phase 1 clinical trials

A

Drugs given to healthy people

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34
Q

What happens in phase 2 clinical trials

A

Treatments given to people with the relevant illness

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35
Q

What happens in phase 3 clinical trials

A

Treatment given to large groups of people in the clinical setting

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36
Q

What happens in phase 4 clinical trials

A

Post market surveillance studies.
Data collected about the drug in different populations.

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37
Q

Definition of evidence based medicine

A

The conscientious, explicit, and judicious use of current best evidence in making decisions about the care of the individual patient

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38
Q

What is internal validity

A

Does the study answer the question? Do the research methods use work?

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39
Q

What is external validity

A

Can the study results be used in real life. To what extent?

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40
Q

What is a studies efficacy?

A

The impact of its intervention under optimum conditions

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41
Q

What is a studies effectiveness

A

Intended/expected effect under ordinary circumstances

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42
Q

Does efficacy show internal or external validity

A

Internal

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43
Q

Does effectiveness show internal or external validity

A

External validity

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44
Q

Benefits of a peer reviewed paper

A

Forces authors to meet standards.
Can be anonymous

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45
Q

Downsides of peer review

A

Longer to print
Harder to get controversial opinions published
Possible to guess anonymous authors

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46
Q

What is the primary hypothesis

A

The hypothesis (often closely related to the clinical Q) which is to be proven true or false.

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47
Q

What is the downside of too much sub group ananlysis

A

Over comparing data (data dredging) leads to increased false statistical significance.

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48
Q

What must confounders be associated with

A

The exposure (but cannot be a consequence of)
The outcome, independently

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49
Q

How to deal with confounders

A

Eliminate
Nullify (spread equally amongst groups)
Account for with stats

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50
Q

What is positive confounding

A

Association between two variables that are not associated

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51
Q

What is a negative confounder

A

Masks an association that is present
(Eg exercise cancelling out smoking)

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52
Q

What does an observational descriptive study do

A

Reports what is seen

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53
Q

What does an observational analytical study do

A

Reports on similarities and differences between experimental and control groups

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54
Q

What does an experimental study do

A

Researchers intervene and report differences between experimental and control group

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55
Q

What does a longitudinal study do

A

Deals with subjects at more than one point in time

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56
Q

What does a cross sectional study do

A

Snapshot of a group at one point in time

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57
Q

What is a parallel study

A

Groups receive different interventions and the experiment proceeds

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58
Q

What does a prospective study do

A

Deals with now and later (looks forward). Data collected as it goes

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59
Q

What does a retrospective study do

A

Deals with now and the past. Pre existing data collected (cheaper!)

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60
Q

What is an ecological study

A

Population study. All information at population level.

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61
Q

What is an exploratory study

A

Ideal setting to see if something works.(New drug, homogenous subjects, placebo use, efficacy data)

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62
Q

Pragmatic study

A

Ordinary setting, see if something works in real life
(Effectiveness data, often new and old tx compared)

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63
Q

What is an (observational analytical) cohort study

A

Recruit subjects with a risk factor.investigates exposure to the risk.
Can be long + therefore expensive.

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64
Q

What does an (observational analytical) cross sectional study do

A

Looks at prevalence of exposure and outcome at one point in time

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65
Q

What bias is created if poor recruitment or allocation techniques are used

A

Selection bias

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66
Q

Name three main categories for exclusion criteria

A

Too unwell (ie other serious illness, consent issues etc)
May become unwell (Inc pregnancy)
Confounding factors

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67
Q

Issues with too many exclusion criteria?

A

Harder to recruit a sample population (risk type II error)
Diagnostic purity bias (results may not be generalisable to gen pop)

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68
Q

Name 5 sampling methods

A
  1. Random
  2. Systematic
  3. Stratified
  4. Cluster
  5. Convenience (easiest, highest risk!)
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69
Q

What is selection bias

A

When recruitment of a target population that is not representative of the general population

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70
Q

Who introduces sampling bias

A

The researcher

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71
Q

Who introduces response bias

A

The study population

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72
Q

Berkson’s bias/admission rate bias

A

Arises from sample being taken from a hospital setting, but hospital admission does not reflect severity or rate within the community

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73
Q

Diagnostic purity bias

A

Arises from exclusion of comorbidities.
Complexity of cases may not be reflected

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74
Q

Incidence/prevalence bias (Neymans bias)

A

Usually due to time gap between onset and selection - severe disease may kill off people leaving only mild disease behind, meaning the data does not contain the sickest individuals.

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75
Q

Membership bias?

A

Group membership used to recruit - the group may not be representative.

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76
Q

Historical control bias

A

When subjects and controls are chosen across time, changing definitions may mean the comparison doesn’t work

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77
Q

Resp ones bias occurs when?

A

Individuals volunteering for studies may differ from general pop - IE more health contieous

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78
Q

Other than at recruitment, when else can selection bias occur

A

At allocation to trial arms - should be blind!

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79
Q

Who uses cluster randomisation

A

Public health (primary care sometimes too)

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80
Q

Does true randomisation or adaptive minimisation work better in small studies

A

Adaptive minimisation as it allows better matched groups

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81
Q

What is concealed allocation

A

The researchers cannot predict with any accuracy which group the next recruit will be placed in

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82
Q

Difference between concealed allocation and blinding

A

Concealed allocation is being unaware which group someone enters at recruitment
Blinding is being unaware what treatment is received.

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83
Q

What is propensity score matching

A

When randomisation can’t be used, a propensity score is calculated per entrant and a match found before recruiting. No match no recruit.

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84
Q

What is publication bias

A

Research that does find a difference between two groups is more likely to be published than research that doesn’t.

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85
Q

What increases the placebo effect

A

Larger pills
More pills
Capsules over tablets

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86
Q

What is interviewer bias

A

A non blinded researcher may ask questions differently if they know what group someone is in

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87
Q

Response bias

A

The subjects answer questions the way they think the researcher wants the answer, rather than with their true beliefs

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88
Q

What is the Hawthorne effect

A

Subjects alter their behaviour because there being watched

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89
Q

What is recall bias

A

What is remembered may be selective not full truth

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90
Q

Name 4 observation biases

A

Interview bias
Response bias
Hawthorne effect
Recall bias

91
Q

What is triple blinding

A

The analyst processing the results is also blinded

92
Q

What is a clinical endpoint

A

A measure of a direct clinical outcome such as morbidity, mortality or survival

93
Q

What is a surrogate endpoint

A

A biomarker substitute for a clinical endpoint (such as LDL reduction)

94
Q

What is validity

A

The extent to which a test measures what it is supposed to measure

95
Q

What is reliability

A

How consistent a test is on repeated measurements

96
Q

When does a test have incremental validity

A

When it helps more than if it were not used

97
Q

What is a systemic measurement error

A

A consistent error made in a series of repetitive tests
Eg a calibration error

98
Q

What do systematic errors reduce

A

Accuracy

99
Q

What is a random error

A

A variable error that occurs in a set of repeated tests

100
Q

What does a random error reduce

A

Precision

101
Q

What are random errors and systematic errors examples of

A

Reliability

102
Q

What is a good cirelation coefficient in a test-retest reliability

A

> 0.7-0.8

103
Q

What is parallel form reliability

A

Repeating the test with an equivalent alternate test

104
Q

What is a parameter

A

Any numerical quantity that standardises a population

105
Q

What is a variable

A

Ant entity which can take on different values (such as gender, drug dose)

106
Q

What is an independent variable

A

The variable manipulated in the study

107
Q

What is a dependent variable

A

What is affected by the change in the independent variable - also known as outcome variable

108
Q

What is a descriptive statistic

A

Summary of data from the sample population

109
Q

What is an inferential statistic

A

Using sample population data to make generalisations about the target population

110
Q

What is incidence

A

The rate of occurrence of new cases over a period of time in a defined population

111
Q

What is mortality rate

A

Risk of death over a period of time in a given population

112
Q

What is morbidity rate

A

The rate of occurrence of new non fatal cases of a disease in a defined population over a given length of time

113
Q

What is morbidity rate

A

The rate of occurrence of new non fatal cases of a disease in a defined population over a given length of time

114
Q

What is a standardised morbidity/mortality rate

A

When the rate is adjusted for a confounder

115
Q

What is point prevalence

A

The proportion of a defined population having the disease at any given point in time

116
Q

What is period prevalence

A

The proportion of a population that has the disease over a given timeframe

117
Q

Relationship between incidence and prevalence

A

Prevalence = incidence x disease average timeframe

118
Q

What is lifetime prevalence

A

Proportion of the population that either has or has had the disease

119
Q

What is qualitative data

A

Categorical or non numerical data - eg gender, colour

120
Q

What is quantitative data

A

Numerical data
Can either be discrete (counts) or continuous

121
Q

What is a nominal scale

A

Organised categories with no relationships to each other (ie hair colour)

122
Q

What is an ordinal scale

A

Categories with an inherent rank, but no number value so the gap between categories is meaningless

123
Q

What is interval scales

A

Organised in a meaningful way, with differences on points being equal accros the scale. DOES NOT start at 0.

124
Q

What is a ratio scale

A

Differences between points equal across the scale but does have a true zero (zero is the start IE Kelvin)

125
Q

What scales use parametric tests

A

Nominal and ordinal scales

126
Q

What scales use non parametric tests

A

Interval and ratio

127
Q

Does a normal distribution have the same mean, median and mode

A

Yes (bell curve)

128
Q

What are binomial and poisons distributions?

A

For use with discrete numbers (IE coin toss, baby born)

129
Q

What is mode

A

Most common value

130
Q

What is frequency

A

Number of values in each category

131
Q

What is a gaussian distribution

A

A normal distribution (bell curve)

132
Q

What are the axis on the bell curve

A

X = variable (IE grade)
Y = frequency

133
Q

What is the mean

A

The sum of all the values divided by number of values

134
Q

What is variance

A

The average distance by which each individual observation differs from the mean

135
Q

What is standard deviation

A

The degree of data spread about the mean

136
Q

What does standard deviation measure

A

Precision

137
Q

How many observations are included in 1,2,3 standard deviations?

A

68%
95%
>99%

138
Q

What is a z score

A

Converts the value of an observation into the number of standard deviations the observation lies from the mean of the distribution

139
Q

What is coefficient or variant for

A

Comparing studies using different units

140
Q

What is a standard normal distribution used for

A

A special case where the mean is 0 and the SD is 1 and area under the curve is 1. Used for comparisons of different means by showing on the same scale

141
Q

Easy ways to tell if a distribution is normsl

A

Plotted it looks bell shaped
Mean median and mode are the same

142
Q

What is the median

A

The middle number in the data

143
Q

What is the range

A

Difference between lowest and highest set

144
Q

What is interquartile range

A

Used in non-normal data, looks at middle 50%

145
Q

Benefits of interquartile range over range

A

Not influenced by outliers

146
Q

What is a coefficient of skewness

A

A measure of symmetry

147
Q

What is a positively skewed distribution

A

Extended tail to the right, mean is larger than median is larger than mode

148
Q

What is central limit theorem

A

The mean of a large number of random variables is distributed approx. Normally.

149
Q

What is the standard error of the mean

A

Often just standard error, it is the standard deviation of the sample means.

150
Q

What is a 95% confidence interval

A

A range in which we are 95% sure the true population results lie.

151
Q

What does it mean if a confidence interval includes zero

A

The results are statistically insignificant
(Ie 3cm +/- 4cm)

152
Q

What does a relative risk value of 1 mean?

A

The results are statistically insignificant

153
Q

What is the positive square root of the variance

A

The standard deviation (standard variance)

154
Q

What is the positive square root of the variance

A

The standard deviation (standard variance)

155
Q

What sort of data can a t-test be used for

A

Normal distribution data ONLY

156
Q

What is parametric data

A

Normally distributed data

157
Q

What is non-parametric data

A

Non-normal distribution data

158
Q

What is a per-protocol analysis

A

Only data from those who complied with trial protocol through to completion are considered

159
Q

What bias can be included with use of a per-protocol analysis

A

Attrition/exclusion bias

160
Q

What is the issue with attrition bias

A

People may drop out due to intolerable side effects
A drug may look more effective than it actually is

161
Q

What is an intention to treat analysis

A

All subjects are included in the analysis, regardless of whether they completed the study

162
Q

What is risk

A

The probability of something happening

163
Q

What is odds

A

Another way of expressing chance

164
Q

What is absolute risk

A

Incidence rate of the outcome

165
Q

What is the absolute risk reduction

A

The drop between the at risk group and the control group

166
Q

Whst does and odds ratio of 1 reflect

A

No effect

167
Q

What does a log odds ratio of zero mean

A

No effect

168
Q

What is the null hypothesis

A

That any difference is due to chance

169
Q

What is the alpha level

A

How rare results would have to be that it is unlikely to be explained by chance( the null hypothesis)

170
Q

What number is alpha usually set to

A

0.05 (or 5%)

171
Q

What number is alpha usually set to

A

0.05 (or 5%)

172
Q

What is a p-value

A

P value expresses the probability of getting a result by chance

173
Q

When can the null hypothesis be rejected

A

When the p value is so small it is below the alpha value - the results are statistically significant

174
Q

What is a type 1 error

A

A false positive result (wrongful rejection)

175
Q

What is a type 2 error

A

A false negative - a wrongful acceptance

176
Q

What contributes to type 1 errors

A

(false positives)
Bias, confounding, multiple hypothesis testing (data dredging)

177
Q

What can cause type 2 errors

A

(false negatives)
Sample size too small

178
Q

What type of error should you consider when accepting the null hypothesis

A

Type 2 error (false negatives)

179
Q

What type of error should you consider when rejection Ng the null hypothesis

A

Type 1 error (false positive)

180
Q

What is power

A

The probability that a type 2 error will not be made

181
Q

What is the range for power

A

0-1

182
Q

What power is generally accepted as being adequate?

A

0.8

183
Q

What does a power of 0.8 mean?

A

There is an 80% probability of finding a significant difference with a given sample size, if the difference exists

184
Q

What is the risk of a type 2 error in a study with a power of 0.8

A

20%

185
Q

What increases power

A

Decreased variability
Larger sample sizes

186
Q

What is a two tailed test

A

Results of interest can go in either direction

187
Q

When should a one tailed test be ysed

A

When a result can only go in one direction

188
Q

What does bonferroni’s correction do

A

Safeguard against multiple tests of statistical significance which might give a a false significance

189
Q

Is statistical significance the same as clinical significance

A

No.
Clinical significance assessed whether treatment affects are worth it in real life

190
Q

What is a confidence interval

A

The range of values around a summary statistics that we are 95% sure the population summary statistic lies
When comparing two groups, if the confidence interval doesn’t overlap this is significant result

191
Q

How to calculate bonferroni’s correction

A

P value divided by number of analyses

192
Q

What is the absolute risk reduction

A

The difference in event rate between the treatment group and the control group

193
Q

What is paired data

A

Data from the same individual at different points in time

194
Q

What tests can you use with categorical data (contingency tables)

A

X*2 and McNemars

195
Q

What is another name for non-parametric data

A

Distribution free statistics

196
Q

What is a useful comparison test for parametric data

A

T-test

197
Q

How to avoid a type 1 error when using student t-test multiple times

A

Use ANOVA instead

198
Q

What does a low fragility index mean

A

A less robust trial outcome

199
Q

What is correlation

A

The strength of a relationship between two variables

200
Q

Explain correlation coefficient R

A

R=0 means no relationship
R between -1 and 1
Positive r positive relationship

201
Q

What is regression

A

Regression expresses the relationship between variables

202
Q

What is a superiority trial

A

Head to head drug trial - new tx better than old?

203
Q

What is Sensitivity

A

True positives

204
Q

What is specifity

A

True negatives

205
Q

What is the positive predictive result

A

The proportion of people who have a positive test who do have the disorder.
(True positive/ true positive + false negatives)

206
Q

What is the accuracy of a test

A

The proportion of people with the correct result

207
Q

Spin and snout?

A

In SPecific tests, Positive results rule IN the disorder.
In SeNsitive tests, Negative results rule OUT the disorder

208
Q

What is the median survival time

A

The time from the start of the study that coincides with a 50% probability of survival

209
Q

What does a forest plot provide

A

Visual evidence of heterogeneity (if present)

210
Q

What sort of paper is a forest plot used in

A

Meta analysis

211
Q

What is a reporting bias

A

Group of biases that can lead to over representation of significant or positive studies in a meta-analysis

212
Q

What study type is most likely to be missed from a systematic review?

A

Small study with negative findings as least likely to be published.
This gives rise to PUBLICATION BIAS

213
Q

How to calculate odds ratio

A

(A/c)/(b/d)
(A is positive case in group one over C negative cases in group 1)
Divided by
(Positive case in group 2 over negative cases in group 2)

214
Q

What is the best test to use if there are two variables to be compared

A

Pearson’s coefficient

215
Q

What is the standard error of the mean

A

The accuracy of which a sample measures a population.
Divide the standard deviation by the square root of the number of patients in the study

216
Q

Negative predictive value?

A

The chance you don’t have the tests if you test negative
So true negatives / true + false negatives

217
Q

What is a chi square test used for

A

Used to compare proportions or percentages

218
Q

What sort of study is the odds ratio associated with

A

Case control study

219
Q

What does a risk ratio less than. 1 mean

A

The measured exposure is protective of the outcome

220
Q

That does a risk ratio >1 mean

A

Measured exposure increases risk of outcome

221
Q

What is the NNT?

A

1/absolute risk reduction

222
Q

How to calculate the absolute risk reduction?

A

Risk in group A - risk in group B

223
Q

How is absolute risk calculated?

A

Number of events in a group/individuals in a group

224
Q

How to calculate the confidence interval

A

Mean +/- (1.96x standard error of the mean)

MFSRH Part 1 CM (15 decks)

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