Stats

Question 1

Explain the two categories of data

Answer 1

Categoric:
Nominal, binary and ordinal

Numeric:
Continuous and discrete

Question 2

Give 3 ways of describing categoric data

Answer 2

Example scenario:
Total participants 676, those using drug and have MI = 31, those using the drug and no MI = 310
Those using placebo and have MI =61 , those using placebo and no MI = 305
Risk for MI with drugs = 31/341 =0.091 (9.1% -just x 100 to get percentage)
Risk for MI with placebo = 61/366 = 0.167 (16.7% to get percentage)
Odds for MI with drugs = 31/310 = 0.1
Odds for MI with placebo = 61/305 = 0.2

(Absolute) risk difference = 0.167 - 0.091 = 0.076 (7.6%) this means the risk with a placebo is 7.6% higher than the drug

Usually just called risk difference but absolute is added when we do not worry about the minus sign

(Relative) Risk ratio = 0.167/0.091 = 1.835 (185%) (placebo on top so becomes focus group), this means the risk is increased by 85% with the placebo compared to the drug, 0.091/0.167 = 0.545 (54.5%) (drug on top so becomes focus group), this means the risk is decreased by 45.5% with the drug than with the placebo

Usually referred to as risk ratio RRR, but actually called relative risk ratio

Odd ratio = 0.2/0.1 = 2 (with the placebo as the focus group) this means that it has increased by 1, there is an 100% increase in the odds of having an MI on the placebo compared to drug A
Odd ration = 0.1/0.2 = 0.5 (with drug A as the focus group) this means that it has decreased by 0.5, so there is a 50% decrease in odds of an MI on drug A compared to the placebo

Question 3

How to find the relative risk of the other focus group e.g think of drug A and placebo scenario

Answer 3

If the risk ratio with the placebo as the focus group is = 1.835
To find the risk ratio with drug A as the focus group, we do 1/1.835 which gives 0.545.
Basically finding the reciprocal

Question 4

Give two ways to measure and present categorical data

Answer 4

Pie charts

Bar charts

Question 5

Give three ways to measure and present numerical (quantitative) data

Answer 5

Dot plots
Histograms
Box and whisker plots (box plots)

Question 6

Give a way to present an association between two continuous variables

Answer 6

Scatter plots

Question 7

Give some characteristics of a histogram

Answer 7

It can be used to show normal distribution (also called Gaussian distribution)

Can show skewed data which is when data is not symmetrical
Negative skewed data = has long low left tail and peaks at high values on the right
Positively skewed data = has long low right tail and peaks at low values on the left

Question 8

Give some characteristics of a box plot

Answer 8

The box contains the middle 50% of the data
The line in the box plot shows the median value
Outliers (which are values 1.5 box length from the upper and lower edge of the box) are plotted as dots outside of the whiskers

Question 9

Give some characteristics of scatter plots

Answer 9

The independent variable is on the X axis and is usually what the experimenter changes

The dependent variable is on the Y axis and is usually the response to what the experimenter changes

Question 10

Giv three ways that measure the spread of data

Answer 10

Range
Inter-quartile range
Standard variation

Question 11

What is the variance

Answer 11

Variance = standard deviation ^2 (squared)

Standard variation = square root of variance

Question 12

What does a large or small standard deviation show

Answer 12

A small standard deviation shows that any random value picked is likely to be close to the mean so small spread of data

A large standard deviation shows that any random value picked is likely to further from the mean so large spread of data

Question 13

What is the best method to use if there is a symmetric distribution of data

Answer 13

Mean and the standard deviation

Question 14

What is the best method to use if the distribution of data is non-symmetric

Answer 14

Median and the interquartile range

Question 15

Methods to summarise categoric variables

Answer 15

Proportion, percentage, risk and odds

Question 16

Methods to summarise numerical (quantitative) data

Answer 16

Mean, median, range, interquartile range and standard deviation

Question 17

Methods to quantify differences between two categorical variables

Answer 17

Absolute risk difference
Relative risk ratio
Odds ratio

Question 18

Methods to quantify the differences between two numeric variables

Answer 18

Persons correlation coefficient (r)
r must be between 1 and -1
\+1 shows a positive linear correlation
0 shows no linear correlation
-1 shows a negative linear correlation

Question 19

Methods to calculate the difference between one categoric variable and one numeric variable

Answer 19

If both variables give symmetrical graphs (distribution of data), use mean - mean =

If one of the variables give a non-symmetrical graph (distribution of data), use median - median =

Question 20

Give the percentage of 1 standard devation, 2 standard deviations and 3 standard deviations.

Answer 20

1 standard deviation = 68%
2 standard deviation = 95.4%
3 standard deviation = 99.8%

Question 21

Which standard deviation give 95% of the distribution in a graph

Answer 21

1.96 standard deviation give 95% of the distribution of the graph

Question 22

If you cannot use a mean for a certain set of data, would you still be able to use standard deviation for that data

Answer 22

No, the standard deviation would be affected by the same issue of being skewed by outliers

All if possible it is always best to use the mean and standard deviation because they include all values in the data so more powerful

Question 23

Who is Sir Galton Francis and what are his contributions to statistics

Answer 23

1822-1911

Standard deviation, correlation, concepts of regression, medians and ranking

First weather map
How to cut a cake
Attractiveness of cities

Question 24

What is standard error

Answer 24

It is an estimate of the precision of the representation of the sample to the population

Question 25

How is the standard error calculated

Answer 25

Standard error = standard deviation/ the square root of the sample size

Question 26

When can the standard error not be used

Answer 26

When the standard deviation and the mean cannot be used due to how skewed the data is

Question 27

What are the rules to use the standard error

Answer 27

The data has to be normally distributed | The sample size has to be large enough (more than 20 individuals)

Question 28

Show how to calculate the confidence interval from the standard error

Answer 28

``` If the Mean = 18,477 sample size (n) = 12 standard deviation (SD) = 3,732 ``` Standard error = standard deviation/ the square root of the sample size Standard error = 1077.3 To get a 95% confidence interval, use the 1.96 from the standard deviation To get a 99% confidence interval, use the 2.58 from the standard deviation Mean - (1.96 x standard error) = 18,477 - (1.96 x 1077.3) = 16,365 Mean + (1.96 x standard error) = 18,477 + (1.96 x 1077.3) = 20,589 95% confident that the true value of the mean lies between 16,365 and 20,589 If we wanted to get the 99% confidence, we would do mean - (2.58 x standard error) and mean + (2.58 x standard error)

Question 29

What does a small standard error mean for a sample

Answer 29

Greater precision that the results from the sample are representative of the populations

Question 30

What does a small standard deviation mean

Answer 30

The values are less spread so there is less variability in the sample

Question 31

What is correlation used to explore

Answer 31

- how two numeric continuous variable are related | - the strength of an association

Question 32

Give the regression equation and what part of it means

Answer 32

Y= a + bx Y is the dependent variable (or called outcome or response) the one we measure e.g blood pressure reading, pain score, hours of sleep X is the independent variable (or called predictor or explanatory) e.g age, deprivation level and family history of illness) A is the y intercept (or called the constant) B is the coefficient - the change in y when we increase x by 1 unit

Question 33

Give the name of the type of regression where the outcome is a single continuous variable e.g sleep time

Answer 33

Linear regression

Question 34

Give the name of a regression which has a binary outcome e.g pass or fail

Answer 34

Logistic regression

Question 35

What is the benefit of regressions compared to just correlations

Answer 35

We can incorporate additional values (additional predictors) which allows us to account for confounding variables

Question 36

Give some characteristics of regression models

Answer 36

- they can be used to create productive models - remove the effects of confounding variables - explore how a particular drug influences the outcome

Question 37

Does linear regression require a binary or numeric outcome variable

Answer 37

It requires a numeric outcome variable

Question 38

A regression model with more than one predictor is called

Answer 38

A multivariable model

Question 39

What is a great benefit of a multivariable regression model (more than one predictor)

Answer 39

It adjusts for confounding variables

Question 40

A difference between coefficients in a single and multiple regression model is

Answer 40

Coefficients in a multiple model have taken account of background factors

Question 41

In linear regression with 1 predictor variable, a coefficient of 1.5 means that increasing the predictor by 1 unit causes

Answer 41

An increase in the outcome by 1.5 units

Question 42

What is prevalence

Answer 42

Proportion of population with a disease at one point in time Number of cases at a point in time/ total population = prevalence

Question 43

What is incidence

Answer 43

A rate Rate at which new cases appear in a population at a certain period of time Number of new cases/ at risk population = incidence

Question 44

Advantages of ecological studies

Answer 44

-uses routinely collected data - Quick, cheap -units of analysis are populations - groups of people -can examine patterns of ill-health by age, sex, ethnicity, country and/or by time -few ethical issues -useful for generating hypotheses

Question 45

Disadvantages of ecological studies

Answer 45

- no link between individual exposure and effect - bias - variation in diagnostic criteria -absence of records of individual attributes -unsuitable format of records -inconsistency in data presentation

Question 46

Advantages of cross-sectional studies

Answer 46

- results used to generate hypotheses -rapid feedback of current events in the community - quick and cheap -few ethical problems

Question 47

Disadvantages of cross-sectional studies

Answer 47

- could just be reporting a medical oddity -prone to bias, e.g. sampling, subject and observer variation - no time reference

Question 48

Advantages of case control studies

Answer 48

-by concentrating effort on the identification of affected individuals and recruiting controls from the unaffected population, the number of subjects required to obtain significant results is kept to a minimum (so good for rare diseases) -results can be obtained relatively quickly because the investigation does not have to wait for the disease to develop (compare this with cohort studies – see later) and can look for multiple causes -it is a relatively inexpensive type of study

Question 49

Disadvantages of case control studies

Answer 49

-generally rely on retrospective data, which has its own dangers. The ability of individuals to recall past events tends to be unreliable due to a tendency for memory to be selective. Records of past events may be incomplete. -because data are collected retrospectively, it is difficult to say if an association is causal or not. This is less of a problem when the exposure is highly specific or where the time between exposure and disease is short -prone to selection and information biases -there can be difficulties choosing controls -the incidence of disease within a population cannot be calculated from this type of study

Question 50

Advantages of cohort study

Answer 50

-the main advantage is that it is possible to distinguish antecedent causes from concurrent associated factors (cause comes before effect) -since incidence can be determined for both exposed and non- exposed groups, we can determine absolute, relative and attributable risks -we can study more than one outcome to the same exposure -there is less chance of bias since exposure is measured before development of disease

Question 51

Disadvantages of cohort study

Answer 51

-cannot be certain that exposures are causal- this requires controlled studies -long periods of study, and large populations mean that cohort studies are expensive -follow-up can be a problem- especially if the period of study is long- this needs to be considered in the design of the study -diagnosis of cases may change over the years as medical science becomes more advanced- better at detecting the disease or with different criteria for a diagnosis

Question 52

Advantages of randomised control trials

Answer 52

-randomization should mean that confounding factors (age, sex etc.) are equally distributed. This helps to concentrate the study on the effect of the intervention -by randomly allocating patients to interventions, it is likely that staff and patients will not break the blinding -statistical tests for significance are easier to interpret when the study design removes confounders -confounders and many biases minimised

Question 53

Disadvantages of randomised control trials

Answer 53

-to allow sufficient numbers to balance confounders these tend to be large and expensive trials. They are often multicentre and may even be multinational -there is always a chance that volunteer bias will be a problem: what about people that refuse to be included in the trial or those that are never asked. -there may be ethical difficulties in withholding treatment from the control group or offering what is believed to be an inferior treatment to one group -may lose statistical power if poor compliance

Question 54

What is critical appraisal

Answer 54

-critical appraisal is the assessment of evidence by systematically reviewing its relevance, validity and results to specific situations -by R Chambers 1998

Question 55

Difference between parametric and non parametric analysis tests

Answer 55

Parametric tests have rules that need to be followed or assumptions that need to be met Non-parametric tests are used as an alternative - they dont need rules to be followed or assumptions to be met Assumptions include - sample size, normal distribution and linearity in regression

Question 56

Examples of parametric test

Answer 56

- one sample t-tests - two sample t-tests (also called students t-test) - chi square test - ANOVA test - Pearson correlation coefficient

Question 57

Examples of non-parametric test

Answer 57

- one sample Wilcoxon test - Mann-Whitney U test - Fishers Exact test - Kruskal-Wallis ANOVA - Spearman rank correlation coefficient

Question 58

Give two examples of critical appraisal tools

Answer 58

- CASP | - AXIS has 20 questions and no scoring system

Question 59

Give the frequency of these single gene defects | Cystic fibrosis, alpha-1-antitrypsin deficiency, Hereditary Haemorrhagic Telengretasia (HHT), Immotile cilia syndrome

Answer 59

Cystic fibrosis = 1 in 2500 alpha-1-antitrypsin deficiency 1 in 2000 Hereditary Haemorrhagic Telengretasia (HHT) 1 in 4000 Immotile cilia syndrome 1 in 20000

Question 60

How can the CFTR gene (chromosome 7, 27 exons and 1480 residue proteins) be identified

Answer 60

- linkage - positional cloning - sequencing

Question 61

How can Cystic Fibrosis be diagnosed

Answer 61

- sweat test | - gene mutation analysis

Question 62

Give the symptoms that Cystic Fibrosis could cause

Answer 62

- abnormal ion transport across epithelium - salt loss - impaired mucociliary clearance - chronic infections - sterility (infertility) - impaired digestion (meconium ileus) - failure to thrive - liver disease - diabetes

Question 63

Treatment of Cystic Fibrosis

Answer 63

- pancreatic enzyme supplementation - control of infection - suppression of chronic infection - antibiotic nebulisers - bronchodilation - salbutamol nebulisers - anti-inflammatory - azithromycin - diabetes - insulin - vaccinations - flu, pneumococcal

Question 64

Give chromosomal cause of alpha-1-antitrypsin

Answer 64

- autosomal recessive - chromosome 14 - 14q32.1

Question 65

What is the normal phenotype for alpha-1-antitrypsin deficiency and the disease phenotype

Answer 65

M is the normal phenotype | S and Z are associated with major disease presentation

Question 66

What are the clinical presentation of alpha-1-antitrypsin deficiency

Answer 66

Due to build up of deformed alpha-1-antitrypsin in the liver - childhood jaundice - early onset cirrhosis Due to the unopposed action of neutrophil elastase in the lungs -early onset emphysema and bronchietasis Highly sensitive to cigarette smoke

Question 67

What is the inheritance pattern of hereditary haemorrhagic talengiectasia (HHT)

Answer 67

Hereditary haemorrhagic talengiectasis (HHT) is also known as Osler-Weber-Rendu diseases (or syndrome) -causes abnormal blood vessel formation in the skin, mucous membranes and in the organs such as the lungs, liver and brain

Question 68

Give the loci affected by the 3 forms of Osler-Weber-Rendu Syndrome and symptoms experienced in these conditions

Answer 68

HHT1 -endoglin gene (ENG) on chromosome 9 HHT2 -ALK-1 HHT3 -chromosome 5 - talengectasia - epitaxis - PAVMs - GI blood loss

Question 69

Give another name for immotile cilia syndrome and its inheritance patterns

Answer 69

- Kartagner's syndrome or primary ciliary dyskinesia | - autosomal recessive

Question 70

Give some symptoms of Kartagner's syndrome

Answer 70

10 variations in dynein arm - infertility - sinusitis - bronchiectasis - situs invertus

Question 71

Give some examples of disease from polygenic influences

Answer 71

- asthma - chronic obstructive pulmonary disease (COPD) - venous thrombosis and pulmonary embolism - Tuberculosis - sarcoidosis (NRAMP) - Obstructive sleep apnoea - infant respiratory distress

Question 72

Give 4 examples of autosomal recessive respiratory disease and their genes

Answer 72

- cystic fibrosis - CFTR - alpha-1-antitrypsin - SERPINEA1 - kartagener's syndrome (immotile cilia) - DNA1 - pulmonary veno-occlusive disease - E1FZAK4

Question 73

Give an x linked example of a respiratory condition and their genes

Answer 73

-chronic granulomatosis disease CYBB

Question 74

Give 2 examples of autosomal dominant conditions and their genes

Answer 74

- hereditary haemorrhagic telangectasis (HHT) - ALK, ENG | - hereditary pulmonary arterial hypertension (HPAH) - BMPR2

Question 75

What is secondary prevention

Answer 75

-aims to detect early disease in order to alter the course of the disease e.g screening by mammography for breast cancer in order to treat it early

Question 76

What is sensitivity and give the formula to calculate it

Answer 76

-the proportion of people with the disease who are correctly identified by the screening test True positive/ true positive + false negative = sensitivity

Question 77

What is specificity

Answer 77

-the proportion of people without the disease are correctly excluded by the screening test True negative/ true negative + false positive = specificity

Question 78

What is positive predictive value and give the formula to calculate it

Answer 78

-the proportion of people with a positive test result who actually have the disease True positive/ true positive + false positive = positive predictive value

Question 79

What is a negative predictive value and give the formula to calculate it

Answer 79

-the proportion of people with a negative test result who do not have the disease True negative/false negative + true negative = negative predictive value

Question 80

Give the formula to calculate prevalence

Answer 80

True positive + false negative = true positive + false negative + false positive + true negative

Question 81

Which of these have an effect the predictive values - prevalence - specificity - sensitivity

Answer 81

- predictive values are dependent on prevalence | - sensitivity and specificity do not affect predictive values

Question 82

How would screening programs be evaluated

Answer 82

-by randomised controlled trial (individual or clusters)

Question 83

Give 3 forms of bias that can affect evaluation of screening programs

Answer 83

- selection bias - lead time bias - length time bias (or length bias)

Question 84

What is selection bias

Answer 84

-people who chose to participate in screening programmes may be different from those who do not - may be at more risk - may be at less risk

Question 85

What is lead time bias

Answer 85

When screening appears to increase survival time because disease was discovered and diagnosed earlier

Question 86

What is length time bias

Answer 86

An overestimation of survival because long duration cases are more likely to be detected and treated than short duration cases e.g PSA screening more likely to be detected as the tumour is slow growing

Question 87

What are the 5 types of screenings

Answer 87

- population-based screening programs (national diabetes and hypertension screening like in thailand) - opportunistic screenings (prevention and control of substance abuse) - screening for communicable diseases (heaf test) - pre-employment and occupational medicals (vision test for commercial drivers) - commercially provided screening (screening is a programme not a test)