EBVM

Question 1

what are the 2 objectives of observational studies

Answer 1

1. identify risk factors
2. quantify the effect of risk factors on disease occurrence

Question 2

what are 3 sources of data for analysis

Answer 2

1. experimental studies
2. observational studies
3. other people’s data (secondary data)

Question 3

in this type of study, a researcher will control one or more factors that may affect what they are studying

Answer 3

experimental studies

Question 4

in this type of study, the research will record factors of interest and outcomes; however these studies don’t change anything

Answer 4

observational studies

Question 5

this type of data describe a property of individuals such as hair color, eye color, religion or gender

Answer 5

categorical

Question 6

this type of data can be put in an order but not measured like a number (ex: sad < ok < happy; BCS)

Answer 6

ordinal (ranked)

Question 7

this is data that exists as whole numbers, such as counts of animals, age or number of times an animal was sick

Answer 7

discrete

Question 8

this is data where any number could be measured, including decimals or fractions (weight, length, age, temp)

Answer 8

continuous

Question 9

numbers are put in order and we find the numbers that are 1 quarter and 3 quarters along, the difference between them is this

Answer 9

interquartile range (IQR)

Question 10

this is the mathematical measure of spread that look at how all the numbers differ from the overall mean

Answer 10

standard deviation (SD)

Question 11

this is a way to express uncertainty in an estimate and show how precise it is; it is a measure of hoe much estimates of that size would vary

Answer 11

standard error

Question 12

this is a precision or uncertainty statement that we add after an estimate; it gives a range which we are reasonably confident will contain the true population value/parameter

Answer 12

confidence interval

Question 13

this is a hypothesis that we are setting out to disprove; normally one of no-difference or no-effect

Answer 13

null hypothesis

Question 14

this is the probability/chance that the difference we have found between our samples would occur if our null hypothesis were true and there was no difference between our populations

Answer 14

P-value

Question 15

if the p-value a researcher gets for their question is less than this critical value, they conclude that there is evidence to reject the null hypothesis

Answer 15

0.05

Question 16

this error is made if we reject a true null hypothesis

Answer 16

type 1 error

Question 17

this error is made if we fail to reject a false null hypothesis

Answer 17

type 2 error

Question 18

a powerful study has a low chance of type 2 error; power is influenced by these 3 things..

Answer 18

1. sample size
2. difference between the populations
3. individual variation

Question 19

list Koch’s postulates; an organism is causal if…

Answer 19

1. present in all cases of disease
2. does not occur in other diseases
3. can be isolated and cultured
4. can induce disease in healthy animals

Question 20

what are 5 difficulties with Koch’s postulates

Answer 20

1. requires specificity of response (only 1 disease)
2. isolation difficult
3. reproduction of disease difficult
4. only applicable to infectious diseases
5. multifactorial complexes cannot be addressed

Question 21

main measures to quantify disease are of these 2 things

Answer 21

morbidity and mortality

Question 22

what is the cumulative incidence (CI) fraction?

Answer 22

CI = number of individuals that become diseased during a particular period / number of healthy individuals in the population at the beginning of that period

Question 23

what is the incidence rate (I) fraction?

Answer 23

I = number of cases of disease that occur in a population during a particular period of time / the sum, over all individuals, of the length of time at risk of developing disease

Question 24

what is the relationship between incidence and prevalence?

Answer 24

P ∝ I x D

Question 25

how to calculate case fatality (CF)?

Answer 25

CF = number of deaths / number of diseased animals

Question 26

how to calculate survival?

Answer 26

S = (number of cases - number of deaths) / number of cases

Question 27

why can’t seronegative animals be included in geometric mean titres?

Answer 27

because the logarithm of zero is -∞

Question 28

what is the geometric titre mean

Answer 28

antilog2 of arithmetic mean

Question 29

these assays are based on ‘all-or-none’ response (ex agglutination)

Answer 29

quantal assays