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Epidemiology > Epi Midterm > Flashcards

Epi Midterm Flashcards

1
Q

ANOVA

A

analysis of variance

best used for:
parametric, interval data, 3 or more groups

example:
effect of a medication on white blood cells in 3 different groups

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2
Q

students t-test

A

best used for:
parametric, nominal data, 2 groups

example:
effects of a diet in two different groups

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3
Q

Chi square

A

best used for:
nonparametric, nominal data, 2 groups

example:
assessing number of people who are exposed to a food type who acquire a food borne illness

used in analysis of contingency tables

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4
Q

Mann Whitney

A

best used for:
nonparametric, ordinal, 2 groups

used for clinical scores

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5
Q

Odds ratio

A

tells you the odds of developing a disease due to exposure

used in retrospective studies

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6
Q

Relative risk

A

rate of disease in exposed divided by the rate of disease in unexposed

used in prospective studies

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7
Q

Fishers exact

A

best used for:
nonparametric, nominal data, 2 groups, SMALL sample sizes

example:
acceptance to vet school between two small groups

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8
Q

wilcoxon rank sum test

A

best used for:

nonparametric, nominal data, 2 groups

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9
Q

example of a study in which multiple regression could be used?

A

changes in white blood cell count in dogs with a certain disease receiving either no treatment, drug A, or drug B

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10
Q

positive predictive value

A

probability that subjects with a positive screening test truly have the disease

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11
Q

negative predictive value

A

probability that subjects with a negative screening test truly don’t have the disease

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12
Q

adjusted rate

A

rate that is adjusted to eliminate the effects of a confounding variable

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13
Q

null hypothesis

A

Ho
there is no difference between the exposed group and the unexposed group

there is no association between variable A and variable B

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14
Q

incidence rate

A

the number of NEW cases of a disease in a population in a specified time period

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15
Q

hawthorne effect

A

participants alter behavior as a result of being in the study

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16
Q

healthy worker effect

A

workers are generally healthier and have lower disease rates than the general population as those who are disabled or physically ill cannot do the work

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17
Q

type I error

A

Alpha

rejecting the null hypothesis when it should be accepted

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18
Q

type II error

A

Beta

accepting the null hypothesis when it should be rejected

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19
Q

amplifying host

A

increases the chance of exposure

example:
infectious agents multiply in the host making infection more likely

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20
Q

second stage relative risk

A

two factors have a high relative risk

need to determine which is the most likely cause

can do so with a 2x2 contingency table

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21
Q

prevalence rate

A

total number of cases (both NEW and OLD) of a disease in a population in a specified time period

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22
Q

volunteer effect

A

form of selection bias

individuals that volunteer to participate in a study are different in some way from the population

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23
Q

p value

A

you are willing to be wrong (in repeated trials) aka to reject the null hypothesis when it should have been accepted 5% of the time

in other words: 95% of the time the observed difference in a population is real and not just due to chance

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24
Q

nominal

A

non quantitative values

examples:
Male, female

25
Q

ordinal

A

represent a rank order

example:
clinical score of severity 1-4

26
Q

interval

A

can interpret the degree of difference between values

example:
white blood cell count

27
Q

cyclic disease pattern

A

periodic changes over several years

casses:
fluctuations in population immunity

28
Q

attributable risk

A

risk difference

the incidence of disease that is directly related to exposure to the determinant

29
Q

secular disease pattern

A

gradual change over a long period of time

causes:
pollution
management changes
slowly spreading agent

30
Q

3 factors that would lead you to conclude that the association between a disease and a determinant was causal?

A

strength of association: large relative risk

temporality: factor occurs in the population before the disease
consistency: similar results from different studies on different populations
specificity: single cause
plausibility: makes sense biologically
coherence: does not conflict with present knowledge

experimental evidence: has been shown in natural experiments

31
Q

incidence vs prevalence

A

incidence is the number of NEW cases

prevalence is the number of NEW and OLD cases

32
Q

Difference between relative risk and odds ratio?

A

relative risk is the relation between disease exposure and non exposure- useful for prospective studies

odds ratio is similar but gives the chances of exposed individuals to develop disease - useful for retrospective studies

33
Q

What can you use a scatter plot for?

A

Shows the relationship between two variables, helps detect outliers

best used with continuous variables

can analyze with a correlation coefficient

34
Q

How can you determine if an outbreak is due to a single source or multiple sources?

A

second stage relative risk

35
Q

When to use fisher’s exact vs chi square

A

Fishers exact should be used with small sample sizes (<5 in each group)

36
Q

What measure of central tendency should be used for each type of data?

A

Nominal – mode
Ordinal - median
Interval - mean

37
Q

Two pitfalls of epidemiologic studies

A

extrapolation: results that are obtained in the study population are extrapolated to the general population

information bias: inadequate medical records, lack of recall

population bias: cases may not be selected properly, example is cases admitted to a hospital for a disease (may be cases of the disease that are not admitted)

38
Q

selection bias

A

relation between exposure and disease is different for participants and non-participants in the study

example: patients die before admission to the hospital

39
Q

information bias

A

measurement error in assessment of exposure or disease

example:
loss of follow-up
incomplete medical records

40
Q

prevarication bias

A

lying

example:
members of a religious group may lie about drinking

41
Q

confounding

A

distortion of an effect of an exposure because it is mixed with the effects of an extraneous factor

42
Q

What does “power” mean and how do you use it in study design?

A

probability of rejecting the null hypothesis when it should be rejected

1-beta

can be used to determine sample size

43
Q

What are two things that influence a secular disease pattern?

A

new diagnostic tests
increased life expectancy
high prevalence in one area

44
Q

How is the concept of target organ helpful in an outbreak investigation?

A

easier to direct the investigation towards a more specific area

will hopefully make it easier to detect the source of the outbreak

45
Q

Advantages and disadvantages of prospective studies

A

Advantages:
establish incidence
true relative risk
assess more than one outcome

disadvantages:
expensive
small number of determinants
time delay in results

46
Q

Advantages and disadvantages of retrospective studies

A

advantages:
inexpensive/quick
rare conditions
many determinants

disadvantages:
information may not be available
time sequence not known

47
Q

types of disease transmission

A

direct: vector infects host
indirect: fomite, disease is acquired from something the vector touched

48
Q

How can you determine estimate of incubation period from an outbreak curve?

A

time from the earliest part of the curve to the peak of the curve

49
Q

Important characteristics of a diagnostic test?

A

highly sensitive
accurate
repeatable

50
Q

skewness

A

measure of asymmetry of distribution curve

51
Q

kurtosis

A

measure of the peakedness of the curve

52
Q

endemic disease

A

occurs with predictable regularity

53
Q

sporadic disease

A

occurs rarely and without regularity

54
Q

epidemic disease

A

occurrence of a disease in a population in excess of what is normally expected

55
Q

common source epidemic

A

all cases within one incubation period

example:
food borne illness

56
Q

propagated epidemic

A

progressive epidemic

example:
infectious disease with animal-animal spread

57
Q

diurnal disease pattern

A

changes that occur over a short period of time

58
Q

bias

A

systematic error in data collection or evaluation that leads to an incorrect result

Epidemiology (1 decks)

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