5. Screening and sampling Flashcards

(31 cards)

1
Q

Why is screening important?

A

one health and public health are focused on prevention

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2
Q

screening tests desirable qualities

A

condition screened needs to be important

screening test should have a high benefit cost ratio

condition needs to be sufficiently prevalent

an effective treatment should be avalible

screening test should have precision and accuracy

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3
Q

precision

A

ability of a measuring instrument to give consistent results on repeated trials

reliability

all shots in the same space not on bulls eye

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4
Q

accuracy

A

the ability of the measuring instrument to give a true interpretation of reality

validity

All shots hit bulls eye

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5
Q

precision and accuracy

A

its not possible to be imprecise and accurate

is possible for a measure to be precise and inaccurate

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6
Q

how to measure accuracy

A

sensitivity = ability to detect disease

specificity = ability to detect the absence of disease

positive predictive value = likelihood of disease giving positive result amount of true positive among positive results

negative predictive value = no disease giving negative results true negatives among all negative results

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7
Q

characteristic of good screening test

A

high in sensitivity high in specificity high in positive predicted value and high in negative predictive value

unealistic

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8
Q

realistic characteristics of screening test

A

tend to be very sensitive so you can be confident in negative result

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9
Q

realistic characteristic of confirmatory test

A

tend to be very specific minimizes false positive

can be confident in positive results

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10
Q

what is the gold standard?

A

the truth which we compare our tests to

definitive diagnostic test that considered best available

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11
Q

chart for gold standard

A
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12
Q

sensitivity equation

A

probability of the test being positive when the disease is actually present

true positives/ true positives + false negatives

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13
Q

specificity equation

A

the probability of a test correctly classifying an individual as disease free

true negatives / true negatives + false positives

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14
Q

positive predictive value equation

A

probability of a patient actually having a disease when the test is positive

true positives / true positives + false positives

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15
Q

negative predictive value

A

probability of a patient being healthy when the test is negative

true negatives / true negatives + false negatives

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16
Q

diagnoses are made based on what characteristics

A

clinical signs, history

regional prevalence of disease

presence of vectors

test attributes

17
Q

high PPV

A

common disease –> positive result –> probability true positive = high PPV

18
Q

low PPV

A

rare disease –> positive results –> probably false positive = Low PPV

19
Q

why sample?

A

compared to using entire population at risk sampling

costs less
less field time
acceptable accuracy
when its impossible to study entire population

20
Q

two sampling schemes

A

random sampling
non randome sampling

21
Q

random sampling

A

every element from the entire population has an equal probability of being selected

22
Q

non random population

A

probability of being chosen is unknown
less expensive
makes statistical analysis and error id more defficult

23
Q

types of random sampling

A

simple random sampling
systemic random sampling
cluster sampling
multi stage sampling

24
Q

types of non random sampling

A

convenience sample = sample is selected because they are easily accessible

snowball = friend

purposive sampling = you choose who you think

quota sampling

25
components of total deviation
26
sampling bias
sampled population is not representative of overall population failure to allow for statistical weighing of samples of unequal popbability
27
sampling error
difference between survey result and population value due to random nature of sample influenced by size and scheme of sample
28
measures of sample error
confidence limits standard error coefficient of variance p values others
29
sampling error used to measure
sample size prior to sample determine how sure you are of analytic results
30
total deviation
total deviation = bias +error
31
bias vs sampling error
bias = is due to mistake than cane be avoided cannot be precisely meausred sampling error = unavoidable when sampling can be calculated after sample