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Epidemiology > Epi Midterm > Flashcards

Epi Midterm Flashcards

(58 cards)

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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

Study These Flashcards
A

non quantitative values

examples:
Male, female

25
ordinal
represent a rank order example: clinical score of severity 1-4
26
interval
can interpret the degree of difference between values example: white blood cell count
27
cyclic disease pattern
periodic changes over several years casses: fluctuations in population immunity
28
attributable risk
risk difference the incidence of disease that is directly related to exposure to the determinant
29
secular disease pattern
gradual change over a long period of time causes: pollution management changes slowly spreading agent
30
3 factors that would lead you to conclude that the association between a disease and a determinant was causal?
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
incidence vs prevalence
incidence is the number of NEW cases prevalence is the number of NEW and OLD cases
32
Difference between relative risk and odds ratio?
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
What can you use a scatter plot for?
Shows the relationship between two variables, helps detect outliers best used with continuous variables can analyze with a correlation coefficient
34
How can you determine if an outbreak is due to a single source or multiple sources?
second stage relative risk
35
When to use fisher’s exact vs chi square
Fishers exact should be used with small sample sizes (<5 in each group)
36
What measure of central tendency should be used for each type of data?
Nominal – mode Ordinal - median Interval - mean
37
Two pitfalls of epidemiologic studies
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
selection bias
relation between exposure and disease is different for participants and non-participants in the study example: patients die before admission to the hospital
39
information bias
measurement error in assessment of exposure or disease example: loss of follow-up incomplete medical records
40
prevarication bias
lying example: members of a religious group may lie about drinking
41
confounding
distortion of an effect of an exposure because it is mixed with the effects of an extraneous factor
42
What does “power” mean and how do you use it in study design?
probability of rejecting the null hypothesis when it should be rejected 1-beta can be used to determine sample size
43
What are two things that influence a secular disease pattern?
new diagnostic tests increased life expectancy high prevalence in one area
44
How is the concept of target organ helpful in an outbreak investigation?
easier to direct the investigation towards a more specific area will hopefully make it easier to detect the source of the outbreak
45
Advantages and disadvantages of prospective studies
Advantages: establish incidence true relative risk assess more than one outcome disadvantages: expensive small number of determinants time delay in results
46
Advantages and disadvantages of retrospective studies
advantages: inexpensive/quick rare conditions many determinants disadvantages: information may not be available time sequence not known
47
types of disease transmission
direct: vector infects host indirect: fomite, disease is acquired from something the vector touched
48
How can you determine estimate of incubation period from an outbreak curve?
time from the earliest part of the curve to the peak of the curve
49
Important characteristics of a diagnostic test?
highly sensitive accurate repeatable
50
skewness
measure of asymmetry of distribution curve
51
kurtosis
measure of the peakedness of the curve
52
endemic disease
occurs with predictable regularity
53
sporadic disease
occurs rarely and without regularity
54
epidemic disease
occurrence of a disease in a population in excess of what is normally expected
55
common source epidemic
all cases within one incubation period example: food borne illness
56
propagated epidemic
progressive epidemic example: infectious disease with animal-animal spread
57
diurnal disease pattern
changes that occur over a short period of time
58
bias
systematic error in data collection or evaluation that leads to an incorrect result

Epidemiology (1 decks)

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